changeset 2:72053397bd45 draft

Uploaded
author fubar
date Mon, 19 Jan 2015 22:09:10 -0500
parents 17a83efb37f9
children 4cf80e2e07bf
files hairpinTool.R hairpinTool.xml readme.rst test-data/screen2-sample_anno.txt test-data/screen2-target_anno.txt test-data/shrnaseq_zuber_test.html test-data/zuber-count_matrix.txt test-data/zuber-sample_anno.txt test-data/zuber-target_anno.txt tool_dependencies.xml
diffstat 10 files changed, 0 insertions(+), 4194 deletions(-) [+]
line wrap: on
line diff
--- a/hairpinTool.R	Mon Jan 19 22:08:26 2015 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,1069 +0,0 @@
-#!/usr/bin/env Rscript
-# ARGS: 1.inputType         -String specifying format of input (fastq or table)
-#    IF inputType is "fastq" or "pairedFastq:
-#       2*.fastqPath        -One or more strings specifying path to fastq files
-#       2.annoPath          -String specifying path to hairpin annotation table
-#       3.samplePath        -String specifying path to sample annotation table
-#       4.barStart          -Integer specifying starting position of barcode
-#       5.barEnd            -Integer specifying ending position of barcode
-#    ###   
-#    IF inputType is "pairedFastq":
-#       6.barStartRev       -Integer specifying starting position of barcode
-#                            on reverse end
-#       7.barEndRev         -Integer specifying ending position of barcode
-#                            on reverse end
-#    ### 
-#       8.hpStart           -Integer specifying startins position of hairpin
-#                            unique region
-#       9.hpEnd             -Integer specifying ending position of hairpin
-#                            unique region
-#    IF inputType is "counts":
-#       2.countPath         -String specifying path to count table
-#       3.annoPath          -String specifying path to hairpin annotation table
-#       4.samplePath        -String specifying path to sample annotation table
-#    ###
-#       10.secFactName      -String specifying name of secondary factor
-#       11.cpmReq           -Float specifying cpm requirement
-#       12.sampleReq        -Integer specifying cpm requirement
-#       13.readReq          -Integer specifying read requirement
-#       14.fdrThresh        -Float specifying the FDR requirement
-#       15.lfcThresh        -Float specifying the log-fold-change requirement
-#       16.workMode         -String specifying exact test or GLM usage
-#       17.htmlPath         -String specifying path to HTML file
-#       18.folderPath       -String specifying path to folder for output
-#    IF workMode is "classic" (exact test)
-#       19.pairData[2]      -String specifying first group for exact test
-#       20.pairData[1]      -String specifying second group for exact test
-#    ###
-#    IF workMode is "glm"
-#       19.contrastData     -String specifying contrasts to be made
-#       20.roastOpt         -String specifying usage of gene-wise tests
-#       21.hairpinReq       -String specifying hairpin requirement for gene-
-#                            wise test
-#       22.selectOpt        -String specifying type of selection for barcode
-#                            plots
-#       23.selectVals       -String specifying members selected for barcode
-#                            plots
-#    ###
-#
-# OUT:  Bar Plot of Counts Per Index
-#       Bar Plot of Counts Per Hairpin
-#       MDS Plot
-#       BCV Plot
-#       Smear Plot
-#       Barcode Plots (If Genewise testing was selected)
-#       Top Expression Table
-#       Feature Counts Table
-#       HTML file linking to the ouputs
-#
-# Author: Shian Su - registertonysu@gmail.com - Jan 2014
-
-# Record starting time
-timeStart <- as.character(Sys.time())
-options(bitmapType='cairo')
-# needed to prevent missing x11 errors for png()
-# Loading and checking required packages
-library(methods, quietly=TRUE, warn.conflicts=FALSE)
-library(statmod, quietly=TRUE, warn.conflicts=FALSE)
-library(splines, quietly=TRUE, warn.conflicts=FALSE)
-library(edgeR, quietly=TRUE, warn.conflicts=FALSE)
-library(limma, quietly=TRUE, warn.conflicts=FALSE)
-
-if (packageVersion("edgeR") < "3.7.17") {
-  stop("Please update 'edgeR' to version >= 3.7.17 to run this tool")
-}
-
-if (packageVersion("limma")<"3.21.16") {
-  message("Update 'limma' to version >= 3.21.16 to see updated barcode graphs")
-}
-
-################################################################################
-### Function declarations
-################################################################################
-
-# Function to load libaries without messages
-silentLibrary <- function(...) {
-  list <- c(...)
-  for (package in list){
-    suppressPackageStartupMessages(library(package, character.only=TRUE))
-  }
-}
-
-# Function to sanitise contrast equations so there are no whitespaces
-# surrounding the arithmetic operators, leading or trailing whitespace
-sanitiseEquation <- function(equation) {
-  equation <- gsub(" *[+] *", "+", equation)
-  equation <- gsub(" *[-] *", "-", equation)
-  equation <- gsub(" *[/] *", "/", equation)
-  equation <- gsub(" *[*] *", "*", equation)
-  equation <- gsub("^\\s+|\\s+$", "", equation)
-  return(equation)
-}
-
-# Function to sanitise group information
-sanitiseGroups <- function(string) {
-  string <- gsub(" *[,] *", ",", string)
-  string <- gsub("^\\s+|\\s+$", "", string)
-  return(string)
-}
-
-# Function to change periods to whitespace in a string
-unmake.names <- function(string) {
-  string <- gsub(".", " ", string, fixed=TRUE)
-  return(string)
-}
-
-# Function has string input and generates an output path string
-makeOut <- function(filename) {
-  return(paste0(folderPath, "/", filename))
-}
-
-# Function has string input and generates both a pdf and png output strings
-imgOut <- function(filename) {
-  assign(paste0(filename, "Png"), makeOut(paste0(filename,".png")), 
-         envir=.GlobalEnv)
-  assign(paste0(filename, "Pdf"), makeOut(paste0(filename,".pdf")),
-         envir=.GlobalEnv)
-}
-
-# Create cat function default path set, default seperator empty and appending
-# true by default (Ripped straight from the cat function with altered argument
-# defaults)
-cata <- function(..., file=htmlPath, sep="", fill=FALSE, labels=NULL, 
-                 append=TRUE) {
-  if (is.character(file)) 
-    if (file == "") 
-      file <- stdout()
-  else if (substring(file, 1L, 1L) == "|") {
-    file <- pipe(substring(file, 2L), "w")
-    on.exit(close(file))
-  }
-  else {
-    file <- file(file, ifelse(append, "a", "w"))
-    on.exit(close(file))
-  }
-  .Internal(cat(list(...), file, sep, fill, labels, append))
-}
-
-# Function to write code for html head and title
-HtmlHead <- function(title) {
-  cata("<head>\n")
-  cata("<title>", title, "</title>\n")
-  cata("</head>\n")
-}
-
-# Function to write code for html links
-HtmlLink <- function(address, label=address) {
-  cata("<a href=\"", address, "\" target=\"_blank\">", label, "</a><br />\n")
-}
-
-# Function to write code for html images
-HtmlImage <- function(source, label=source, height=600, width=600) {
-  cata("<img src=\"", source, "\" alt=\"", label, "\" height=\"", height)
-  cata("\" width=\"", width, "\"/>\n")
-}
-
-# Function to write code for html list items
-ListItem <- function(...) {
-  cata("<li>", ..., "</li>\n")
-}
-
-TableItem <- function(...) {
-  cata("<td>", ..., "</td>\n")
-}
-
-TableHeadItem <- function(...) {
-  cata("<th>", ..., "</th>\n")
-}
-################################################################################
-### Input Processing
-################################################################################
-
-# Grabbing arguments from command line
-argv <- commandArgs(T)
-
-inputType <- as.character(argv[1])
-if (inputType == "fastq") {
-
-  fastqPath <- as.character(gsub("fastq::", "", argv[grepl("fastq::", argv)], 
-                                 fixed=TRUE))
-
-  # Remove fastq paths
-  argv <- argv[!grepl("fastq::", argv, fixed=TRUE)] 
-
-  fastqPathRev <- NULL
-  annoPath <- as.character(argv[2])
-  samplePath <- as.character(argv[3])
-  barStart <- as.numeric(argv[4])
-  barEnd <- as.numeric(argv[5])
-  barStartRev <- NULL
-  barStartRev <- NULL
-  hpStart <- as.numeric(argv[8])
-  hpEnd <- as.numeric(argv[9])
-} else if (inputType=="pairedFastq") {
-
-  fastqPath <- as.character(gsub("fastq::", "", argv[grepl("fastq::", argv)], 
-                                 fixed=TRUE))
-  
-  fastqPathRev <- as.character(gsub("fastqRev::", "", 
-                               argv[grepl("fastqRev::", argv)], fixed=TRUE))
-
-  # Remove fastq paths
-  argv <- argv[!grepl("fastq::", argv, fixed=TRUE)]
-  argv <- argv[!grepl("fastqRev::", argv, fixed=TRUE)] 
-
-  annoPath <- as.character(argv[2])
-  samplePath <- as.character(argv[3])
-  barStart <- as.numeric(argv[4])
-  barEnd <- as.numeric(argv[5])
-  barStartRev <- as.numeric(argv[6])
-  barEndRev <- as.numeric(argv[7])
-  hpStart <- as.numeric(argv[8])
-  hpEnd <- as.numeric(argv[9])
-} else if (inputType == "counts") {
-  countPath <- as.character(argv[2])
-  annoPath <- as.character(argv[3])
-  samplePath <- as.character(argv[4])
-}
-
-secFactName <- as.character(argv[10])
-cpmReq <- as.numeric(argv[11])
-sampleReq <- as.numeric(argv[12])
-readReq <- as.numeric(argv[13])
-fdrThresh <- as.numeric(argv[14])
-lfcThresh <- as.numeric(argv[15])
-selectDirection <- as.character(argv[16])
-workMode <- as.character(argv[17])
-htmlPath <- as.character(argv[18])
-folderPath <- as.character(argv[19])
-
-if (workMode == "classic") {
-  pairData <- character()
-  pairData[2] <- as.character(argv[20])
-  pairData[1] <- as.character(argv[21])
-} else if (workMode == "glm") {
-  contrastData <- as.character(argv[20])
-  roastOpt <- as.character(argv[21])
-  hairpinReq <- as.numeric(argv[22])
-  selectOpt <- as.character(argv[23])
-  selectVals <- as.character(argv[24])
-}
-
-# Read in inputs
-
-samples <- read.table(samplePath, header=TRUE, sep="\t")
-
-anno <- read.table(annoPath, header=TRUE, sep="\t")
-
-if (inputType == "counts") {
-  counts <- read.table(countPath, header=TRUE, sep="\t")
-}
-
-###################### Check inputs for correctness ############################
-samples$ID <- make.names(samples$ID)
-
-if ( !any(grepl("group", names(samples))) ) {
-  stop("'group' column not specified in sample annotation file")
-} # Check if grouping variable has been specified
-
-if (secFactName != "none") {
-  if ( !any(grepl(secFactName, names(samples))) ) {
-  tempStr <- paste0("Second factor specified as \"", secFactName, "\" but ",
-                    "no such column name found in sample annotation file")
-  stop(tempStr)
-  } # Check if specified secondary factor is present 
-}
-
-
-if ( any(table(samples$ID) > 1) ){
-  tab <- table(samples$ID)
-  offenders <- paste(names(tab[tab > 1]), collapse=", ")
-  offenders <- unmake.names(offenders)
-  stop("'ID' column of sample annotation must have unique values, values ",
-       offenders, " are repeated")
-} # Check that IDs in sample annotation are unique
-
-if (inputType == "fastq" || inputType == "pairedFastq") {
-  
-  if ( any(table(anno$ID) > 1) ){
-    tab <- table(anno$ID)
-    offenders <- paste(names(tab[tab>1]), collapse=", ")
-    stop("'ID' column of hairpin annotation must have unique values, values ",
-    offenders, " are repeated")
-  } # Check that IDs in hairpin annotation are unique
-  
-} else if (inputType == "counts") {
-  # The first element of the colnames will be 'ID' and should not match
-  idFromSample <- samples$ID
-  idFromTable <- colnames(counts)[-1]
-  if (any(is.na(match(idFromTable, idFromSample)))) {
-    stop("not all samples have groups specified")
-  } # Check that a group has be specifed for each sample
-  
-  if ( any(table(counts$ID) > 1) ){
-    tab <- table(counts$ID)
-    offenders <- paste(names(tab[tab>1]), collapse=", ")
-    stop("'ID' column of count table must have unique values, values ",
-    offenders, " are repeated")
-  } # Check that IDs in count table are unique
-}
-if (workMode == "glm") {
-  if (roastOpt == "yes") {
-    if (is.na(match("Gene", colnames(anno)))) {
-      tempStr <- paste("Gene-wise tests selected but'Gene' column not",
-                       "specified in hairpin annotation file")
-      stop(tempStr)
-    }
-  }
-}
-
-if (secFactName != "none") {
-  if (workMode != "glm") {
-    tempStr <- paste("only glm analysis type possible when secondary factor",
-                     "used, please change appropriate option.")
-  }
-}
-
-################################################################################
-
-# Process arguments
-if (workMode == "glm") {
-  if (roastOpt == "yes") {
-    wantRoast <- TRUE
-  } else {
-    wantRoast <- FALSE
-  }
-}
-
-# Split up contrasts seperated by comma into a vector and replace spaces with
-# periods
-if (exists("contrastData")) {
-  contrastData <- unlist(strsplit(contrastData, split=","))
-  contrastData <- sanitiseEquation(contrastData)
-  contrastData <- gsub(" ", ".", contrastData, fixed=TRUE)
-}
-
-# Replace spaces with periods in pair data
-if (exists("pairData")) {
-  pairData <- make.names(pairData)
-}
-
-# Generate output folder and paths
-dir.create(folderPath, showWarnings=FALSE)
-
-# Generate links for outputs
-imgOut("barHairpin")
-imgOut("barIndex")
-imgOut("mds")
-imgOut("bcv")
-if (workMode == "classic") {
-  smearPng <- makeOut(paste0("smear(", pairData[2], "-", pairData[1],").png"))
-  smearPdf <- makeOut(paste0("smear(", pairData[2], "-", pairData[1],").pdf"))
-  topOut <- makeOut(paste0("toptag(", pairData[2], "-", pairData[1],").tsv"))
-} else if (workMode == "glm") {
-  smearPng <- character()
-  smearPdf <- character()
-  topOut <- character()
-  roastOut <- character()
-  barcodePng <- character()
-  barcodePdf <- character()
-  for (i in 1:length(contrastData)) {
-    smearPng[i] <- makeOut(paste0("smear(", contrastData[i], ").png"))
-    smearPdf[i] <- makeOut(paste0("smear(", contrastData[i], ").pdf"))
-    topOut[i] <- makeOut(paste0("toptag(", contrastData[i], ").tsv"))
-    roastOut[i] <- makeOut(paste0("gene_level(", contrastData[i], ").tsv"))
-    barcodePng[i] <- makeOut(paste0("barcode(", contrastData[i], ").png"))
-    barcodePdf[i] <- makeOut(paste0("barcode(", contrastData[i], ").pdf"))
-  }
-}
-countsOut <- makeOut("counts.tsv")
-sessionOut <- makeOut("session_info.txt")
-
-# Initialise data for html links and images, table with the link label and
-# link address
-linkData <- data.frame(Label=character(), Link=character(),
-                       stringsAsFactors=FALSE)
-imageData <- data.frame(Label=character(), Link=character(),
-                        stringsAsFactors=FALSE)
-                        
-# Initialise vectors for storage of up/down/neutral regulated counts
-upCount <- numeric()
-downCount <- numeric()
-flatCount <- numeric()
-
-################################################################################
-### Data Processing
-################################################################################
-
-# Transform gene selection from string into index values for mroast
-if (workMode == "glm") {
-  if (selectOpt == "rank") {
-    selectVals <- gsub(" ", "", selectVals, fixed=TRUE)
-    selectVals <- unlist(strsplit(selectVals, ","))
-    
-    for (i in 1:length(selectVals)) {
-      if (grepl(":", selectVals[i], fixed=TRUE)) {
-        temp <- unlist(strsplit(selectVals[i], ":"))
-        selectVals <- selectVals[-i]
-        a <- as.numeric(temp[1])
-        b <- as.numeric(temp[2])
-        selectVals <- c(selectVals, a:b)         
-      }
-    }
-    selectVals <- as.numeric(unique(selectVals))
-  } else {
-    selectVals <- gsub(" ", "", selectVals, fixed=TRUE)
-    selectVals <- unlist(strsplit(selectVals, ","))
-  }                                                           
-}
-                                                  
-if (inputType == "fastq" || inputType == "pairedFastq") {
-  # Use EdgeR hairpin process and capture outputs
-
-  hpReadout <- capture.output(
-  data <- processAmplicons(readfile=fastqPath, readfile2=fastqPathRev,
-                            barcodefile=samplePath, 
-                            hairpinfile=annoPath,
-                            barcodeStart=barStart, barcodeEnd=barEnd,
-                            barcodeStartRev=barStartRev, 
-                            barcodeEndRev=barEndRev,
-                            hairpinStart=hpStart, hairpinEnd=hpEnd, 
-                            verbose=TRUE)
-  )
-
-  # Remove function output entries that show processing data or is empty
-  hpReadout <- hpReadout[hpReadout!=""]
-  hpReadout <- hpReadout[!grepl("Processing", hpReadout)]
-  hpReadout <- hpReadout[!grepl("in file", hpReadout)]
-  hpReadout <- gsub(" -- ", "", hpReadout, fixed=TRUE)
-
-  # Make the names of groups syntactically valid (replace spaces with periods)
-  data$samples$group <- make.names(data$samples$group)
-  if (secFactName != "none") {
-    data$samples[[secFactName]] <- make.names(data$samples[[secFactName]])
-  }
-} else if (inputType == "counts") {
-  # Process counts information, set ID column to be row names
-  rownames(counts) <- counts$ID
-  counts <- counts[ , !(colnames(counts) == "ID")]
-  countsRows <- nrow(counts)
-  
-  # Process group information
-  sampleNames <- colnames(counts)
-  matchedIndex <- match(sampleNames, samples$ID)
-  factors <- samples$group[matchedIndex]
-
-  if (secFactName != "none") {
-    secFactors <- samples[[secFactName]][matchedIndex]
-  }
-  
-  annoRows <- nrow(anno)
-  anno <- anno[match(rownames(counts), anno$ID), ]
-  annoMatched <- sum(!is.na(anno$ID))
-  
-  if (any(is.na(anno$ID))) {
-    warningStr <- paste("count table contained more hairpins than",
-                        "specified in hairpin annotation file")
-    warning(warningStr)
-  }
-  
-  # Filter out rows with zero counts
-  sel <- rowSums(counts)!=0
-  counts <- counts[sel, ]
-  anno <- anno[sel, ]
-  
-  # Create DGEList
-  data <- DGEList(counts=counts, lib.size=colSums(counts), 
-                  norm.factors=rep(1,ncol(counts)), genes=anno, group=factors)
-  
-  # Make the names of groups syntactically valid (replace spaces with periods)
-  data$samples$group <- make.names(data$samples$group)
-}
-
-# Filter out any samples with zero counts
-if (any(data$samples$lib.size == 0)) {
-  sampleSel <- data$samples$lib.size != 0
-  filteredSamples <- paste(data$samples$ID[!sampleSel], collapse=", ")
-  data$counts <- data$counts[, sampleSel]
-  data$samples <- data$samples[sampleSel, ]
-}
-
-# Filter hairpins with low counts
-preFilterCount <- nrow(data)
-selRow <- rowSums(cpm(data$counts) > cpmReq) >= sampleReq
-selCol <- colSums(data$counts) > readReq
-data <- data[selRow, selCol]
-
-# Check if any data survived filtering
-if (length(data$counts) == 0) {
-  stop("no data remains after filtering, consider relaxing filters")
-}
-
-# Count number of filtered tags and samples
-postFilterCount <- nrow(data)
-filteredCount <- preFilterCount - postFilterCount
-sampleFilterCount <- sum(!selCol)
-
-if (secFactName == "none") {
-  # Estimate dispersions
-  data <- estimateDisp(data)
-  commonBCV <- round(sqrt(data$common.dispersion), 4)
-} else {
-  # Construct design
-  if (inputType == "counts") {
-      
-    sampleNames <- colnames(counts)
-    matchedIndex <- match(sampleNames, samples$ID)
-    factors <- factor(make.names(samples$group[matchedIndex]))
-
-    secFactors <- factor(make.names(samples[[secFactName]][matchedIndex]))
-
-  } else if (inputType == "fastq" || inputType == "pairedFastq") {
-
-    factors <- factor(data$sample$group)
-    secFactors <- factor(data$sample[[secFactName]])
-  
-  }
-
-  design <- model.matrix(~0 + factors + secFactors)
-  
-  # Estimate dispersions
-  data <- estimateDisp(data, design=design)
-  commonBCV <- round(sqrt(data$common.dispersion), 4)
-}
-
-
-################################################################################
-### Output Processing
-################################################################################
-
-# Plot number of hairpins that could be matched per sample
-png(barIndexPng, width=600, height=600)
-barplot(height<-colSums(data$counts), las=2, main="Counts per index", 
-        cex.names=1.0, cex.axis=0.8, ylim=c(0, max(height)*1.2))
-imageData[1, ] <- c("Counts per Index", "barIndex.png")
-invisible(dev.off())
-
-pdf(barIndexPdf)
-barplot(height<-colSums(data$counts), las=2, main="Counts per index", 
-        cex.names=1.0, cex.axis=0.8, ylim=c(0, max(height)*1.2))
-linkData[1, ] <- c("Counts per Index Barplot (.pdf)", "barIndex.pdf")
-invisible(dev.off())
-
-# Plot per hairpin totals across all samples
-png(barHairpinPng, width=600, height=600)
-if (nrow(data$counts)<50) {
-  barplot(height<-rowSums(data$counts), las=2, main="Counts per hairpin",
-          cex.names=0.8, cex.axis=0.8, ylim=c(0, max(height)*1.2))
-} else {
-  barplot(height<-rowSums(data$counts), las=2, main="Counts per hairpin",
-          cex.names=0.8, cex.axis=0.8, ylim=c(0, max(height)*1.2),
-          names.arg=FALSE)
-}
-imageData <- rbind(imageData, c("Counts per Hairpin", "barHairpin.png"))
-invisible(dev.off())
-
-pdf(barHairpinPdf)
-if (nrow(data$counts)<50) {
-  barplot(height<-rowSums(data$counts), las=2, main="Counts per hairpin",
-          cex.names=0.8, cex.axis=0.8, ylim=c(0, max(height)*1.2))
-} else {
-  barplot(height<-rowSums(data$counts), las=2, main="Counts per hairpin",
-          cex.names=0.8, cex.axis=0.8, ylim=c(0, max(height)*1.2),
-          names.arg=FALSE)
-}
-newEntry <- c("Counts per Hairpin Barplot (.pdf)", "barHairpin.pdf")
-linkData <- rbind(linkData, newEntry)
-invisible(dev.off())
-
-# Make an MDS plot to visualise relationships between replicate samples
-png(mdsPng, width=600, height=600)
-plotMDS(data, labels=data$samples$group, col=as.numeric(data$samples$group), main="MDS Plot")
-imageData <- rbind(imageData, c("MDS Plot", "mds.png"))
-invisible(dev.off())
-
-pdf(mdsPdf)
-plotMDS(data, labels=data$samples$group, col=as.numeric(data$samples$group),main="MDS Plot")
-newEntry <- c("MDS Plot (.pdf)", "mds.pdf")
-linkData <- rbind(linkData, newEntry)
-invisible(dev.off())
-
-# BCV Plot
-png(bcvPng, width=600, height=600)
-plotBCV(data, main="BCV Plot")
-imageData <- rbind(imageData, c("BCV Plot", "bcv.png"))
-invisible(dev.off())
-
-pdf(bcvPdf)
-plotBCV(data, main="BCV Plot")
-newEntry <- c("BCV Plot (.pdf)", "bcv.pdf")
-linkData <- rbind(linkData, newEntry)
-invisible(dev.off())
-
-if (workMode == "classic") {
-  # Assess differential representation using classic exact testing methodology 
-  # in edgeR
-  testData <- exactTest(data, pair=pairData)
-  
-  top <- topTags(testData, n=Inf)
-
-  if (selectDirection == "all") {
-    topIDs <- top$table[(top$table$FDR < fdrThresh) &
-                      (abs(top$table$logFC) > lfcThresh), 1]
-  } else if (selectDirection == "up") {
-    topIDs <- top$table[(top$table$FDR < fdrThresh) &
-                      (top$table$logFC > lfcThresh), 1]
-  } else if (selectDirection == "down") {
-  topIDs <- top$table[(top$table$FDR < fdrThresh) &
-                      (top$table$logFC < -lfcThresh), 1]
-}
-                      
-  write.table(top, file=topOut, row.names=FALSE, sep="\t")
-  
-  linkName <- paste0("Top Tags Table(", pairData[2], "-", pairData[1], 
-                     ") (.tsv)")
-  linkAddr <- paste0("toptag(", pairData[2], "-", pairData[1], ").tsv")
-  linkData <- rbind(linkData, c(linkName, linkAddr))
-  
-  upCount[1] <- sum(top$table$FDR < fdrThresh & top$table$logFC > lfcThresh)
-
-  downCount[1] <- sum(top$table$FDR < fdrThresh & 
-                      top$table$logFC < -lfcThresh)
-
-  flatCount[1] <- sum(top$table$FDR > fdrThresh |
-                      abs(top$table$logFC) < lfcThresh)
-  
-  
-  
-  # Select hairpins with FDR < 0.05 to highlight on plot
-  png(smearPng, width=600, height=600)
-  plotTitle <- gsub(".", " ", 
-                    paste0("Smear Plot: ", pairData[2], "-", pairData[1]),
-                    fixed=TRUE)
-  plotSmear(testData, de.tags=topIDs, 
-            pch=20, cex=1.0, main=plotTitle)
-  abline(h=c(-1, 0, 1), col=c("dodgerblue", "yellow", "dodgerblue"), lty=2)
-  imgName <- paste0("Smear Plot(", pairData[2], "-", pairData[1], ")")
-  imgAddr <- paste0("smear(", pairData[2], "-", pairData[1],").png")
-  imageData <- rbind(imageData, c(imgName, imgAddr))
-  invisible(dev.off())
-  
-  pdf(smearPdf)
-  plotTitle <- gsub(".", " ", 
-                    paste0("Smear Plot: ", pairData[2], "-", pairData[1]),
-                    fixed=TRUE)
-  plotSmear(testData, de.tags=topIDs, 
-            pch=20, cex=1.0, main=plotTitle)
-  abline(h=c(-1, 0, 1), col=c("dodgerblue", "yellow", "dodgerblue"), lty=2)
-  imgName <- paste0("Smear Plot(", pairData[2], "-", pairData[1], ") (.pdf)")
-  imgAddr <- paste0("smear(", pairData[2], "-", pairData[1], ").pdf")
-  linkData <- rbind(linkData, c(imgName, imgAddr))
-  invisible(dev.off())
-  
-} else if (workMode == "glm") {
-  # Generating design information
-  if (secFactName == "none") {
-
-    factors <- factor(data$sample$group)
-    design <- model.matrix(~0 + factors)
-    
-    colnames(design) <- gsub("factors", "", colnames(design), fixed=TRUE)
-
-  } else {
-
-    factors <- factor(data$sample$group)
-
-    if (inputType == "counts") {
-      
-      sampleNames <- colnames(counts)
-      matchedIndex <- match(sampleNames, samples$ID)
-      factors <- factor(samples$group[matchedIndex])
-
-      secFactors <- factor(samples[[secFactName]][matchedIndex])
-
-    } else if (inputType == "fastq" || inputType == "pairedFastq") {
-
-      secFactors <- factor(data$sample[[secFactName]])
-    
-    }
-
-    design <- model.matrix(~0 + factors + secFactors)
-    
-    colnames(design) <- gsub("factors", "", colnames(design), fixed=TRUE)
-    colnames(design) <- gsub("secFactors", secFactName, colnames(design), 
-                              fixed=TRUE)
-  }
-  
-  
-  # Split up contrasts seperated by comma into a vector
-  contrastData <- unlist(strsplit(contrastData, split=","))
-  
-  for (i in 1:length(contrastData)) {
-    # Generate contrasts information
-    contrasts <- makeContrasts(contrasts=contrastData[i], levels=design)
-    
-    # Fit negative bionomial GLM
-    fit <- glmFit(data, design)
-    # Carry out Likelihood ratio test
-    testData <- glmLRT(fit, contrast=contrasts)
-    
-    # Select hairpins with FDR < 0.05 to highlight on plot
-    top <- topTags(testData, n=Inf)
-
-    if (selectDirection == "all") {
-      topIDs <- top$table[(top$table$FDR < fdrThresh) &
-                        (abs(top$table$logFC) > lfcThresh), 1]
-    } else if (selectDirection == "up") {
-      topIDs <- top$table[(top$table$FDR < fdrThresh) &
-                        (top$table$logFC > lfcThresh), 1]
-    } else if (selectDirection == "down") {
-      topIDs <- top$table[(top$table$FDR < fdrThresh) &
-                        (top$table$logFC < -lfcThresh), 1]
-    }
-
-    write.table(top, file=topOut[i], row.names=FALSE, sep="\t")
-    
-    linkName <- paste0("Top Tags Table(", contrastData[i], ") (.tsv)")
-    linkAddr <- paste0("toptag(", contrastData[i], ").tsv")
-    linkData <- rbind(linkData, c(linkName, linkAddr))
-    
-    # Collect counts for differential representation
-    upCount[i] <- sum(top$table$FDR < fdrThresh & top$table$logFC > lfcThresh)
-    downCount[i] <- sum(top$table$FDR < fdrThresh & 
-                        top$table$logFC < -lfcThresh)
-    flatCount[i] <- sum(top$table$FDR > fdrThresh |
-                        abs(top$table$logFC) < lfcThresh)
-    
-    # Make a plot of logFC versus logCPM
-    png(smearPng[i], height=600, width=600)
-    plotTitle <- paste("Smear Plot:", gsub(".", " ", contrastData[i], 
-                       fixed=TRUE))
-    plotSmear(testData, de.tags=topIDs, pch=20, cex=0.8, main=plotTitle)
-    abline(h=c(-1, 0, 1), col=c("dodgerblue", "yellow", "dodgerblue"), lty=2)
-    
-    imgName <- paste0("Smear Plot(", contrastData[i], ")")
-    imgAddr <- paste0("smear(", contrastData[i], ").png")
-    imageData <- rbind(imageData, c(imgName, imgAddr))
-    invisible(dev.off())
-    
-    pdf(smearPdf[i])
-    plotTitle <- paste("Smear Plot:", gsub(".", " ", contrastData[i], 
-                       fixed=TRUE))
-    plotSmear(testData, de.tags=topIDs, pch=20, cex=0.8, main=plotTitle)
-    abline(h=c(-1, 0, 1), col=c("dodgerblue", "yellow", "dodgerblue"), lty=2)
-    
-    linkName <- paste0("Smear Plot(", contrastData[i], ") (.pdf)")
-    linkAddr <- paste0("smear(", contrastData[i], ").pdf")
-    linkData <- rbind(linkData, c(linkName, linkAddr))
-    invisible(dev.off())
-    
-    genes <- as.character(data$genes$Gene)
-    unq <- unique(genes)
-    unq <- unq[!is.na(unq)]
-    geneList <- list()
-    for (gene in unq) {
-      if (length(which(genes == gene)) >= hairpinReq) {
-        geneList[[gene]] <- which(genes == gene)
-      }
-    }
-    
-    if (wantRoast) {
-      # Input preparaton for roast
-      nrot <- 9999
-      set.seed(602214129)
-      roastData <- mroast(data, index=geneList, design=design,
-                         contrast=contrasts, nrot=nrot)
-      roastData <- cbind(GeneID=rownames(roastData), roastData)
-      write.table(roastData, file=roastOut[i], row.names=FALSE, sep="\t")
-      linkName <- paste0("Gene Level Analysis Table(", contrastData[i], 
-                         ") (.tsv)")
-      linkAddr <- paste0("gene_level(", contrastData[i], ").tsv")
-      linkData <- rbind(linkData, c(linkName, linkAddr))
-      if (selectOpt == "rank") {
-        selectedGenes <- rownames(roastData)[selectVals]
-      } else {
-        selectedGenes <- selectVals
-      }
-      
-      if (packageVersion("limma")<"3.19.19") {
-        png(barcodePng[i], width=600, height=length(selectedGenes)*150)
-      } else {
-        png(barcodePng[i], width=600, height=length(selectedGenes)*300)
-      }
-      par(mfrow=c(length(selectedGenes), 1))
-      for (gene in selectedGenes) {
-        barcodeplot(testData$table$logFC, index=geneList[[gene]],
-                    main=paste("Barcode Plot for", gene, "(logFCs)", 
-                               gsub(".", " ", contrastData[i])),
-                    labels=c("Positive logFC", "Negative logFC"))
-      }
-      imgName <- paste0("Barcode Plot(", contrastData[i], ")")
-      imgAddr <- paste0("barcode(", contrastData[i], ").png")
-      imageData <- rbind(imageData, c(imgName, imgAddr))
-      dev.off()
-      if (packageVersion("limma")<"3.19.19") {
-        pdf(barcodePdf[i], width=8, height=2)
-      } else {
-        pdf(barcodePdf[i], width=8, height=4)
-      }
-      for (gene in selectedGenes) {
-        barcodeplot(testData$table$logFC, index=geneList[[gene]],
-                    main=paste("Barcode Plot for", gene, "(logFCs)", 
-                               gsub(".", " ", contrastData[i])),
-                    labels=c("Positive logFC", "Negative logFC"))
-      }
-      linkName <- paste0("Barcode Plot(", contrastData[i], ") (.pdf)")
-      linkAddr <- paste0("barcode(", contrastData[i], ").pdf")
-      linkData <- rbind(linkData, c(linkName, linkAddr))
-      dev.off()
-    }
-  }
-}
-
-# Generate data frame of the significant differences
-sigDiff <- data.frame(Up=upCount, Flat=flatCount, Down=downCount)
-if (workMode == "glm") {
-
-  row.names(sigDiff) <- contrastData
-
-} else if (workMode == "classic") {
-
-  row.names(sigDiff) <- paste0(pairData[2], "-", pairData[1])
-
-}
-
-# Output table of summarised counts
-ID <- rownames(data$counts)
-outputCounts <- cbind(ID, data$counts)
-write.table(outputCounts, file=countsOut, row.names=FALSE, sep="\t",
-            quote=FALSE)
-linkName <- "Counts table (.tsv)"
-linkAddr <- "counts.tsv"
-linkData <- rbind(linkData, c(linkName, linkAddr))
-
-# Record session info
-writeLines(capture.output(sessionInfo()), sessionOut)
-linkData <- rbind(linkData, c("Session Info", "session_info.txt"))
-
-# Record ending time and calculate total run time
-timeEnd <- as.character(Sys.time())
-timeTaken <- capture.output(round(difftime(timeEnd,timeStart), digits=3))
-timeTaken <- gsub("Time difference of ", "", timeTaken, fixed=TRUE)
-################################################################################
-### HTML Generation
-################################################################################
-# Clear file
-cat("", file=htmlPath)
-
-cata("<html>\n")
-HtmlHead("EdgeR Output")
-
-cata("<body>\n")
-cata("<h3>EdgeR Analysis Output:</h3>\n")
-cata("<h4>Input Summary:</h4>\n")
-if (inputType == "fastq" || inputType == "pairedFastq") {
-
-  cata("<ul>\n")
-  ListItem(hpReadout[1])
-  ListItem(hpReadout[2])
-  cata("</ul>\n")
-  cata(hpReadout[3], "<br />\n")
-  cata("<ul>\n")
-  ListItem(hpReadout[4])
-  ListItem(hpReadout[7])
-  cata("</ul>\n")
-  cata(hpReadout[8:11], sep="<br />\n")
-  cata("<br />\n")
-  cata("<b>Please check that read percentages are consistent with ")
-  cata("expectations.</b><br >\n")
-
-} else if (inputType == "counts") {
-
-  cata("<ul>\n")
-  ListItem("Number of Samples: ", ncol(data$counts))
-  ListItem("Number of Hairpins: ", countsRows)
-  ListItem("Number of annotations provided: ", annoRows)
-  ListItem("Number of annotations matched to hairpin: ", annoMatched)
-  cata("</ul>\n")
-
-}
-
-cata("The estimated common biological coefficient of variation (BCV) is: ", 
-     commonBCV, "<br />\n")
-
-if (secFactName == "none") {
-
-  cata("No secondary factor specified.<br />\n")
-
-} else {
-
-  cata("Secondary factor specified as: ", secFactName, "<br />\n")
-
-}
-
-cata("<h4>Output:</h4>\n")
-cata("PDF copies of JPEGS available in 'Plots' section.<br />\n")
-for (i in 1:nrow(imageData)) {
-  if (grepl("barcode", imageData$Link[i])) {
-
-    if (packageVersion("limma")<"3.19.19") {
-
-      HtmlImage(imageData$Link[i], imageData$Label[i], 
-                height=length(selectedGenes)*150)
-
-    } else {
-
-      HtmlImage(imageData$Link[i], imageData$Label[i], 
-                height=length(selectedGenes)*300)
-
-    }
-  } else {
-
-    HtmlImage(imageData$Link[i], imageData$Label[i])
-
-  }
-}
-cata("<br />\n")
-
-cata("<h4>Differential Representation Counts:</h4>\n")
-
-cata("<table border=\"1\" cellpadding=\"4\">\n")
-cata("<tr>\n")
-TableItem()
-for (i in colnames(sigDiff)) {
-  TableHeadItem(i)
-}
-cata("</tr>\n")
-for (i in 1:nrow(sigDiff)) {
-  cata("<tr>\n")
-  TableHeadItem(unmake.names(row.names(sigDiff)[i]))
-  for (j in 1:ncol(sigDiff)) {
-    TableItem(as.character(sigDiff[i, j]))
-  }
-  cata("</tr>\n")
-}
-cata("</table>")
-
-cata("<h4>Plots:</h4>\n")
-for (i in 1:nrow(linkData)) {
-  if (grepl(".pdf", linkData$Link[i])) {
-    HtmlLink(linkData$Link[i], linkData$Label[i])
-  }
-}
-
-cata("<h4>Tables:</h4>\n")
-for (i in 1:nrow(linkData)) {
-  if (grepl(".tsv", linkData$Link[i])) {
-    HtmlLink(linkData$Link[i], linkData$Label[i])
-  }
-}
-
-cata("<p>Alt-click links to download file.</p>\n")
-cata("<p>Click floppy disc icon on associated history item to download ")
-cata("all files.</p>\n")
-cata("<p>.tsv files can be viewed in Excel or any spreadsheet program.</p>\n")
-
-cata("<h4>Additional Information:</h4>\n")
-
-if (inputType == "fastq") {
-
-  ListItem("Data was gathered from fastq raw read file(s).")
-
-} else if (inputType == "counts") {
-
-  ListItem("Data was gathered from a table of counts.")
-
-}
-
-if (cpmReq != 0 && sampleReq != 0) {
-  tempStr <- paste("Target sequences without more than", cpmReq,
-                   "CPM in at least", sampleReq, "samples are insignificant",
-                   "and filtered out.")
-  ListItem(tempStr)
-
-  filterProp <- round(filteredCount/preFilterCount*100, digits=2)
-  tempStr <- paste0(filteredCount, " of ", preFilterCount," (", filterProp,
-                   "%) target sequences were filtered out for low ",
-                   "count-per-million.")
-  ListItem(tempStr)
-}
-
-if (readReq != 0) {
-  tempStr <- paste("Samples that did not produce more than", readReq,
-                   "counts were filtered out.")
-  ListItem(tempStr)
-
-  tempStr <- paste0(sampleFilterCount, " samples were filtered out for low ",
-                    "counts.")
-  ListItem(tempStr)
-}
-
-if (exists("filteredSamples")) {
-  tempStr <- paste("The following samples were filtered out for having zero",
-                   "library size: ", filteredSamples)
-  ListItem(tempStr)
-}
-
-if (workMode == "classic") {
-  ListItem("An exact test was performed on each target sequence.")
-} else if (workMode == "glm") {
-  ListItem("A generalised linear model was fitted to each target sequence.")
-}
-
-cit <- character()
-link <-character()
-link[1] <- paste0("<a href=\"",
-                  "http://www.bioconductor.org/packages/release/bioc/",
-                  "vignettes/limma/inst/doc/usersguide.pdf",
-                  "\">", "limma User's Guide", "</a>.")
-link[2] <- paste0("<a href=\"",
-                  "http://www.bioconductor.org/packages/release/bioc/",
-                  "vignettes/edgeR/inst/doc/edgeRUsersGuide.pdf",
-                  "\">", "edgeR User's Guide", "</a>")
-                  
-cit[1] <- paste("Robinson MD, McCarthy DJ and Smyth GK (2010).",
-                "edgeR: a Bioconductor package for differential",
-                "expression analysis of digital gene expression",
-                "data. Bioinformatics 26, 139-140")
-cit[2] <- paste("Robinson MD and Smyth GK (2007). Moderated statistical tests",
-                "for assessing differences in tag abundance. Bioinformatics",
-                "23, 2881-2887")
-cit[3] <- paste("Robinson MD and Smyth GK (2008). Small-sample estimation of",
-                "negative binomial dispersion, with applications to SAGE data.",
-                "Biostatistics, 9, 321-332")
-
-cit[4] <- paste("McCarthy DJ, Chen Y and Smyth GK (2012). Differential",
-                "expression analysis of multifactor RNA-Seq experiments with",
-                "respect to biological variation. Nucleic Acids Research 40,",
-                "4288-4297")
-
-cata("<h4>Citations</h4>")
-cata("<ol>\n")
-ListItem(cit[1])
-ListItem(cit[2])
-ListItem(cit[3])
-ListItem(cit[4])
-cata("</ol>\n")
-
-cata("<p>Report problems to: su.s@wehi.edu.au</p>\n")
-
-for (i in 1:nrow(linkData)) {
-  if (grepl("session_info", linkData$Link[i])) {
-    HtmlLink(linkData$Link[i], linkData$Label[i])
-  }
-}
-
-cata("<table border=\"0\">\n")
-cata("<tr>\n")
-TableItem("Task started at:"); TableItem(timeStart)
-cata("</tr>\n")
-cata("<tr>\n")
-TableItem("Task ended at:"); TableItem(timeEnd)
-cata("</tr>\n")
-cata("<tr>\n")
-TableItem("Task run time:"); TableItem(timeTaken)
-cata("<tr>\n")
-cata("</table>\n")
-
-cata("</body>\n")
-cata("</html>")
--- a/hairpinTool.xml	Mon Jan 19 22:08:26 2015 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,645 +0,0 @@
-<?xml version="1.0"?>
-<tool id="shrnaseq" name="shRNAseq" version="1.2.1">
-  <description>
-    for differential representation for shRNAseq and sgRNA
-  </description>
-    
-  <requirements>
-    <requirement type="package" version="3.1.2">R</requirement>
-    <requirement type="package" version="0.1">shrnaseq_r</requirement>
-    <requirement type="set_environment">HAIRPINTOOL_R_SOURCE</requirement>
-  </requirements>
-  
-  <stdio>
-    <exit_code range="1:" level="fatal" description="Tool exception" />
-  </stdio>
-  
-  <command>
-  Rscript \$HAIRPINTOOL_R_SOURCE "$inputOpt.inputType"
-                #if $inputOpt.inputType=="fastq":
-
-                  #for $i, $fas in enumerate($inputOpt.fastq):
-                    fastq::$fas.file
-                  #end for
-    
-                  "$inputOpt.hairpin"
-                  "$inputOpt.samples"
-
-                  #if $inputOpt.positions.posOption=="yes":
-                    $inputOpt.positions.barstart
-                    $inputOpt.positions.barend
-                    0
-                    0
-                    $inputOpt.positions.hpstart
-                    $inputOpt.positions.hpend
-                  #else:
-                    1
-                    5
-                    0
-                    0
-                    37
-                    57
-                  #end if
-                #elif $inputOpt.inputType=="pairedFastq":
-
-                  #for $i, $fas in enumerate($inputOpt.fastq):
-                    fastq::$fas.file
-                  #end for
-
-                  #for $i, $fas in enumerate($inputOpt.fastq):
-                    fastqRev::$fas.fileRev
-                  #end for
-    
-                  "$inputOpt.hairpin"
-                  "$inputOpt.samples"
-                    
-                  #if $inputOpt.positions.posOption=="yes":
-                    $inputOpt.positions.barstart
-                    $inputOpt.positions.barend
-                    $inputOpt.positions.barstartRev
-                    $inputOpt.positions.barendRev
-                    $inputOpt.positions.hpstart
-                    $inputOpt.positions.hpend
-                  #else:
-                    1
-                    5
-                    0
-                    0
-                    37
-                    57
-                  #end if
-
-                #elif $inputOpt.inputType=="counts":
-                  "$inputOpt.counts"
-                  "$inputOpt.hairpin"
-                  "$inputOpt.samples"
-                  0
-                  0
-                  0
-                  0
-                  0
-                #end if
-                
-                #if $inputOpt.secondaryFactor.secFactorOpt=="yes":
-                  "$inputOpt.secondaryFactor.secFactName"
-                #else:
-                  "none"
-                #end if
-
-                #if $filterCPM.filtOption=="yes":
-                  $filterCPM.cpmReq
-                  $filterCPM.sampleReq
-                  $filterCPM.readReq
-                #else:
-                  -Inf
-                  -Inf
-                  -Inf
-                #end if
-          
-                "$fdr"
-                "$lfc"
-                "$direction"
-                "$workMode.mode"
-                "$outFile"
-                "$outFile.files_path"
-          
-                #if $workMode.mode=="classic":
-                  "$workMode.pair1"
-                  "$workMode.pair2"
-                #elif $workMode.mode=="glm":
-                  "$workMode.contrast"
-                  "$workMode.roast.roastOption"
-
-                  #if $workMode.roast.roastOption=="yes":
-                    "$workMode.roast.hairpinReq"
-                    "$workMode.roast.select.selOption"
-                    "$workMode.roast.select.selection"
-                  #else:
-                    0
-                    0
-                    0
-                  #end if
-
-                #end if
-  </command>
-  
-  <inputs>
-    <conditional name="inputOpt">
-
-      <param name="inputType" type="select" label="Input File Type">
-        <option value="fastq">FastQ File</option>
-        <option value="pairedFastq">Paired FastQ File</option>
-        <option value="counts">Table of Counts</option>
-      </param>
-
-      <when value="fastq">
-        <param name="hairpin" type="data" format="tabular" 
-               label="Target Annotation"/>
-        
-        <param name="samples" type="data" format="tabular" 
-               label="Sample Annotation"/>
-               
-        <repeat name="fastq" title="FastQ Files">       
-          <param name="file" type="data" format="fastq"/>
-        </repeat>
-        
-        <conditional name="secondaryFactor">
-          
-          <param name="secFactorOpt" type="select"
-                 label="Include Secondary Factor">
-
-            <option value="no" selected="True">No</option>
-
-            <option value="yes">Yes</option>
-
-          </param>
-
-          <when value="yes">
-
-            <param name="secFactName" type="text" label="Secondary Factor Name"
-                   size="80"/>
-
-          </when>
-
-          <when value="no">
-          </when>
-        </conditional>
-        
-        <conditional name="positions">
-          <param name="posOption" type="select" 
-                 label="Specify Sample Index and Target Sequence Locations?"
-                 help="Default Positions: Index: 1 to 5, Target: 37 to 57.">
-            <option value="no" selected="True">No</option>
-            <option value="yes">Yes</option>
-          </param>
-          
-          <when value="yes">
-            <param name="barstart" type="integer" value="1"
-                   label="Index Starting Position"/>
-            <param name="barend" type="integer" value="5"
-                   label="Index Ending Position"/>
-            
-            <param name="hpstart" type="integer" value="37"
-                   label="Target Starting Position"/>
-               
-            <param name="hpend" type="integer" value="57"
-                   label="Target Ending Position"/>
-          </when>
-          
-          <when value="no"/>
-        </conditional>
-      </when>
-
-      <when value="pairedFastq">
-        <param name="hairpin" type="data" format="tabular" 
-               label="Target Sequence Annotation"/>
-        
-        <param name="samples" type="data" format="tabular" 
-               label="Sample Annotation"/>
-               
-        <repeat name="fastq" title="FastQ Files">       
-          <param name="file" type="data" format="fastq"/>
-          <param name="fileRev" type="data" format="fastq"/>
-        </repeat>
-          
-        <conditional name="secondaryFactor">
-
-          <param name="secFactorOpt" type="select"
-                 label="Include Secondary Factor">
-
-            <option value="no" selected="True">No</option>
-
-            <option value="yes">Yes</option>
-
-          </param>
-
-          <when value="yes">
-
-            <param name="secFactName" type="text" label="Secondary Factor Name"
-                   size="80"/>
-
-          </when>
-
-          <when value="no">
-          </when>
-        </conditional>
-
-        <conditional name="positions">
-
-          <param name="posOption" type="select" 
-                 label="Specify Sample Index and Target Sequence Locations?"
-                 help="Default Positions: Index: 1 to 5, Input required for 
-                       reverse end, Target: 37 to 57.">
-
-            <option value="no" selected="True">No</option>
-
-            <option value="yes">Yes</option>
-
-          </param>
-          
-          <when value="yes">
-            <param name="barstart" type="integer" value="1"
-                   label="Index Starting Position"/>
-
-            <param name="barend" type="integer" value="5"
-                   label="Index Ending Position"/>
-
-            <param name="barstartRev" type="integer" value="0"
-                   label="Reverse Index Starting Position"/>
-                   
-            <param name="barendRev" type="integer" value="0"
-                   label="Reverse Index Ending Position"/>
-           
-            <param name="hpstart" type="integer" value="37"
-                   label="Target Starting Position"/>
-               
-            <param name="hpend" type="integer" value="57"
-                   label="Target Ending Position"/>
-          </when>
-
-          <when value="no">
-          </when>
-
-        </conditional>
-
-      </when>
-
-      <when value="counts">
-
-        <param name="counts" type="data" format="tabular" label="Counts Table"/>
-
-        <param name="hairpin" type="data" format="tabular" 
-               label="Target Sequence Annotation"/>
-
-        <param name="samples" type="data" format="tabular"
-               label="Sample Annotation"/> 
-
-        <conditional name="secondaryFactor">
-
-          <param name="secFactorOpt" type="select"
-                 label="Include Secondary Factor">
-
-            <option value="no" selected="True">No</option>
-
-            <option value="yes">Yes</option>
-
-          </param>
-
-          <when value="yes">
-
-            <param name="secFactName" type="text" label="Secondary Factor Name"
-                   size="80"/>
-
-          </when>
-
-          <when value="no">
-          </when>
-
-        </conditional>
-
-      </when>
-
-    </conditional>
-    
-    <conditional name="filterCPM">
-      <param name="filtOption" type="select" label="Filter Low CPM?"
-       help="Ignore target sequences with very low representation when 
-             performing analysis.">
-        <option value="yes">Yes</option>
-        <option value="no">No</option>
-      </param>
-      
-        <when value="yes">
-          <param name="cpmReq" type="float" value="0.5" min="0"
-                 label="Minimum CPM"/>
-                 
-          <param name="sampleReq" type="integer" value="1" min="0"
-                 label="Minimum Samples" 
-                 help="Filter out all the genes that do not meet the minimum 
-                       CPM in at least this many samples."/>
-
-          <param name="readReq" type="integer" value="1000" min="0"
-                 label="Minimum Reads" 
-                 help="Filter out all samples that do not have the minimum 
-                       number of reads."/>
-
-        </when>
-        
-        <when value="no"/>
-        
-    </conditional>
-    
-    <conditional name="workMode">
-      <param name="mode" type="select" label="Analysis Type"
-       help="Classic Exact Tests are useful for simple comparisons across
-             two sampling groups. Generalised linear models allow for more 
-             complex contrasts and gene level analysis to be made.">
-        <option value="classic">Classic Exact Test</option>
-        <option value="glm">Generalised Linear Model</option>
-      </param>
-      
-      <when value="classic">
-        <param name="pair1" type="text" label="Compare" size="40"/>
-        <param name="pair2" type="text" label="To" size="40"
-               help="The analysis will subtract values of this group from those
-                     in the group above to establish the difference."/>
-      </when>
-      
-      <when value="glm">
-        <param name="contrast" type="text" size="60"
-               label="Contrasts of interest"
-               help="Specify equations defining contrasts to be made. Eg. 
-                     KD-Control will result in positive fold change if KD has
-                     greater expression and negative if Control has greater
-                     expression."/>
-               
-        <conditional name="roast">
-          <param name="roastOption" type="select" 
-                 label="Perform Gene Level Analysis?"
-                 help="Analyse LogFC tendencies for target sequences belonging
-                       to the same gene. NOTE: this is a slow procedure that
-                       scales badly with the number of genes analysed.">
-            <option value="no">No</option>
-            <option value="yes">Yes</option>
-          </param>
-          
-          <when value="yes">
-            <param name="hairpinReq" type="integer" value="2" min="2"
-                   label="Minimum Targets Found"
-                   help="Only genes with at least this many target sequences
-                         found will be analysed."/>
-                         
-            <conditional name="select">
-              <param name="selOption" type="select"
-                     label="Gene Selection Method">
-                <option value="rank">By p-value Rank</option>
-                <option value="geneID">By Gene Identifier</option>
-              </param>
-              <when value="rank">
-                <param name="selection" type="text" size="40" value="1:5"
-                       label="Ranks of Top Genes to Plot"
-                       help="Genes are ranked in ascending p-value for
-                             differential representation, individual ranks can
-                             be entered seperated by comma or a range seperated
-                             by colon."/>
-              </when>
-              <when value="geneID">
-                <param name="selection" type="text" size="80" value=""
-                       label="Symbols of Genes to Plot"
-                       help="Select genes based on their identifier in the
-                             'Gene' column of the sample information file.
-                             Please ensure exact match with the values in input
-                             file and separate selections with commas."/>
-              </when>
-            </conditional>
-
-            
-          </when>
-          
-          <when value="no"/>
-        </conditional>
-      </when>
-    </conditional>
-    
-    <param name="fdr" type="float" value="0.05" min="0" max="1"
-           label="FDR Threshold"
-           help="All observations below this threshold will be highlighted
-                 in the smear plot."/>
-
-    <param name="lfc" type="float" value="0" min="0" 
-           label="Absolute LogFC Threshold"
-           help="In additional to meeting the FDR requirement, the absolute 
-                 value of the log-fold-change of the observation must be above
-                 this threshold to be highlighted."/>
-
-    <param name="direction" type="select" label="Highlight Option"
-        help="Only hightlight positive or negative fold changes in smear plot?">
-        <option value="all">Default</option>
-        <option value="up">Positive Only</option>
-        <option value="down">Negative Only</option>
-    </param>
-  </inputs>
-
-  <outputs>
-    <data format="html" name="outFile" label="TagSeq Analysis"/>
-  </outputs>
-<tests>
-<test>
-    <param name='inputType' value="counts"/>
-    <param name='counts' value='zuber-count_matrix.txt' />
-    <param name='hairpin' value='zuber-target_anno.txt' />
-    <param name='samples' value='zuber-sample_anno.txt' />
-    <param name="secFactorOpt" value='no' />
-    <param name="filtOption" value='no' />
-    <param name="fdr" value='0.05' />
-    <param name="lfc" value="0" />
-    <param name="direction" value="all" />
-    <param name="mode" value="classic" />
-    <param name="pair1" value="Day 0" />
-    <param name="pair2" value="Day 14" />
-    <output name='outFile' file='shrnaseq_zuber_test.html' compare='diff' lines_diff = '10'/>
-</test>
-</tests>
-  <help>
-      
-.. class:: infomark
-
-**What it does**
-
-Given tables containing information about the hairpins/sgRNA and their 
-associated sample indices, information about the samples and fastq file 
-containing the sequencing reads. This tool will generate plots and tables for 
-the analysis of differential representation.
-
-.. class:: infomark
-
-A tutorial of how to use this tool is available at:
-http://bioinf.wehi.edu.au/shRNAseq/galaxy.html
-
------
-
-.. class:: infomark
-
-**INPUTS**
-
-**Input File Type:**
-
-This tool is able to either generate counts from a raw FastQ file given the
-information regarding the samples and hairpins/sgRNA. Alternatively if a table 
-of counts has already been generated it can also be used.
-
-**Counts Table (Counts Input):**
-
-A tab delimited text table of information regarding the counts of 
-hairpins/sgRNA. Should have a column 'ID' to denote the hairpins/sgRNA that 
-counts correspond to. Each additional column should have titles corresponding to 
-the label for the sample.
-
-Example::
-
-  ID  Sample1 Sample2 Sample3
-  Control1 49802 48014 40148
-  Control2 12441 16352 14232
-  Control3 9842  9148  9111
-  Hairpin1 3300  3418  2914
-  Hairpin2 91418 95812 93174
-  Hairpin3 32985 31975 35104
-  Hairpin4 12082 14081 14981
-  Hairpin5 2491  2769  2691
-  Hairpin6 1294  1486  1642
-  Hairpin7 49501 49076 47611
-  ...
-  
-**Target Sequence Annotation:**
-
-A tab delimited text table of information regarding the targetted 
-hairpins/sgRNA sequence. Should have columns 'ID', 'Sequences' and 'Gene' to 
-uniquely identify the target, align it with the reads to produce counts and 
-identify which gene the target acts on.
-
-NOTE: the column names are case sensitive and should be input exactly as they
-are shown here.
-
-Example::
-
-  ID  Sequences Gene
-  Control1  TCTCGCTTGGGCGAGAGTAAG 2
-  Control2  CCGCCTGAAGTCTCTGATTAA 2
-  Control3  AGGAATTATAATGCTTATCTA 2
-  Hairpin1  AAGGCAGAGACTGACCACCTA 4
-  Hairpin2  GAGCGACCTGGTGTTACTCTA 4
-  Hairpin3  ATGGTGTAAATAGAGCTGTTA 4
-  Hairpin4  CAGCTCATCTTCTGTGAAGAA 4
-  Hairpin5  CAGCTCTGTGGGTCAGAAGAA 4
-  Hairpin6  CCAGGCACAGATCTCAAGATA 4
-  Hairpin7  ATGACAAGAAAGACATCTCAA 7
-  ...
-  
-**Sample Annotation (FastQ Input):**
-
-A tab delimited text table of information regarding the samples. Should have
-columns 'ID', 'Sequences' and 'group' to uniquely identify each sample, identify
-the sample in the reads by its sample index sequence and correctly group 
-replicates for analysis. Additional columns may inserted for annotation purposes 
-and will not interfere with analysis as long as the necessary columns are 
-present.
-
-NOTE: With the exception of other_group, column names are case sensitive and
-should be input exactly as they are shown here. The other_group column can be
-named by the user and specified in the "Include Secondary Factor" option of the
-tool.
-
-Example::
-
-  ID  Sequences group other_group Replicate
-  3 GAAAG Day 2 male 1
-  6 GAACC Day 10  female  1
-  9 GAAGA Day 5 GFP neg male 1
-  16  GAATT Day 5 GFP pos male 1
-  18  GACAC Day 2 female 2
-  21  GACCA Day 10  male  2
-  28  GACGT Day 5 GFP neg male 2
-  31  GACTG Day 5 GFP pos female 2
-  33  GAGAA Day 2 male 3
-  40  GAGCT Day 10  female  3
-  ...
-  
-**Include Secondary Factor**
-
-If there are two factors involved in the experiment (i.e. Age and Gender) then
-then secondary factor should be included to improve the statistical analysis.
-The secondary factor should be specified as a column in the sample annotation
-file and the corresponding column name should be input exactly as it is into 
-the provided field in the tool.
-
-NOTE: Currently the secondary factor is used only to improve statistical
-analysis, comparisons can only be made in the primary factor specified as 
-"group" in the sample annotation.
-
-**Specify Sample Index and Target Sequence Locations (FastQ Input):**
-
-It is assumed that in the sequencing reads that the first 5 bases are the
-sample index sequence and that bases 37-57 are the hairpins/sgRNA. If this is 
-not the case then the values of the positions can be changed, however it still
-requires the sample indices and hairpins/sgRNA to be in a consistent location an
-in a continuous sequence.
-
-NOTE: position values start at 1 for the first base.
-
-**Filter Low CPM?:**
-
-Often in a large screen there may members with very low counts which are of no
-interest in the experiment, these may be filtered out to speed up computations.
-Filtering will be based on counts per million in a required number of samples.
-
-**Analysis Type:**
-
- * **Classic Exact Test:** This allows two experimental groups to be compared 
-   and p-values for differential representation derivec for each target 
-   sequence. Simple and fast for straightforward comparisons. In this option you
-   will have the option of "*Compare* x *To* y" which implicitly subtracts the 
-   data from y from that of x to produce the comparison.
-
- * **Generalised Linear Model:** This allow for complex contrasts to be specified 
-   and also gene level analysis to be performed. If this option is chosen then 
-   contrasts must be explicitly stated in equations and multiple contrasts can 
-   be made. In addition there will be the option to analyse hairpins/sgRNA on a 
-   per-gene basis to see if hairpins/sgRNA belonging to a particular gene have 
-   any overall tendencies for the direction of their log-fold-change.
-
-**FDR Threshold:**
-The smear plot in the output will have hairpins/sgRNA highlighted to signify
-significant differential representation. The significance is determined by
-contorlling the false discovery rate, only those with a FDR lower than the
-threshold will be highlighted in the plot.
-
-
------
-
-
-**Citations:**
-
-.. class:: infomark
-
-limma
-
-Please cite the paper below for the limma software itself.  Please also try
-to cite the appropriate methodology articles that describe the statistical
-methods implemented in limma, depending on which limma functions you are
-using.  The methodology articles are listed in Section 2.1 of the limma 
-User's Guide.
-
-  * Smyth, GK (2005). Limma: linear models for microarray data. In: 
-    'Bioinformatics and Computational Biology Solutions using R and 
-    Bioconductor'. R. Gentleman, V. Carey, S. Dudoit, R. Irizarry, 
-    W. Huber (eds), Springer, New York, pages 397-420.
-
-.. class:: infomark
-
-edgeR
-
-Please cite the first paper for the software itself and the other papers for
-the various original statistical methods implemented in edgeR.  See 
-Section 1.2 in the User's Guide for more detail.
-
-  * Robinson MD, McCarthy DJ and Smyth GK (2010). edgeR: a Bioconductor 
-    package for differential expression analysis of digital gene expression 
-    data. Bioinformatics 26, 139-140
-    
-  * Robinson MD and Smyth GK (2007). Moderated statistical tests for assessing 
-    differences in tag abundance. Bioinformatics 23, 2881-2887
-    
-  * Robinson MD and Smyth GK (2008). Small-sample estimation of negative 
-    binomial dispersion, with applications to SAGE data.
-    Biostatistics, 9, 321-332
-    
-  * McCarthy DJ, Chen Y and Smyth GK (2012). Differential expression analysis 
-    of multifactor RNA-Seq experiments with respect to biological variation. 
-    Nucleic Acids Research 40, 4288-4297
-    
-Report problems to: su.s@wehi.edu.au
-
-.. _edgeR: http://www.bioconductor.org/packages/release/bioc/html/edgeR.html
-.. _limma: http://www.bioconductor.org/packages/release/bioc/html/limma.html
-  </help>
-</tool>
--- a/readme.rst	Mon Jan 19 22:08:26 2015 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,15 +0,0 @@
-shrnaseq wrapper
-================
-
-This is a self installing Galaxy tool exposing the shrnaseq_ R package which has excellent documentation at
-shrnaseq_ Minimal details are provided in this wrapper - please RTM to get the best out of it.
-
-
-.. _shrnaseq: http://bioinf.wehi.edu.au/shRNAseq/
-
-Underlying R code written by Matt Ritchie.
-Galaxy wrapper by Shian Su
-Autoinstallation and fixin' : Ross Lazarus
-
-This version first passed tests on 18 Jan 2015
-
--- a/test-data/screen2-sample_anno.txt	Mon Jan 19 22:08:26 2015 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,1 +0,0 @@
-ID	Sequences	group	Replicate
3	GAAAG	Day 2	1
6	GAACC	Day 10	1
9	GAAGA	Day 5 GFP neg	1
16	GAATT	Day 5 GFP pos	1
18	GACAC	Day 2	2
21	GACCA	Day 10	2
28	GACGT	Day 5 GFP neg	2
31	GACTG	Day 5 GFP pos	2
33	GAGAA	Day 2	3
40	GAGCT	Day 10	3
43	GAGGG	Day 5 GFP neg	3
46	GAGTC	Day 5 GFP pos	3
\ No newline at end of file
--- a/test-data/screen2-target_anno.txt	Mon Jan 19 22:08:26 2015 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,138 +0,0 @@
-ID	Sequences	Gene
-Control1	TCTCGCTTGGGCGAGAGTAAG	2
-Control2	CCGCCTGAAGTCTCTGATTAA	2
-Control3	AGGAATTATAATGCTTATCTA	2
-Hairpin1	AAGGCAGAGACTGACCACCTA	4
-Hairpin2	GAGCGACCTGGTGTTACTCTA	4
-Hairpin3	ATGGTGTAAATAGAGCTGTTA	4
-Hairpin4	CAGCTCATCTTCTGTGAAGAA	4
-Hairpin5	CAGCTCTGTGGGTCAGAAGAA	4
-Hairpin6	CCAGGCACAGATCTCAAGATA	4
-Hairpin7	ATGACAAGAAAGACATCTCAA	7
-Hairpin8	GAAGATGATGTTTATGGTTTA	7
-Hairpin9	AAAGACCATAGAGAAGTTCAA	8
-Hairpin10	TAGAGAAGTTCAAGACCATAA	8
-Hairpin11	ACCCTTGATCTTCGAGTGCAA	8
-Hairpin12	CCGAGGATAGTAGGACTTCTA	8
-Hairpin13	CTGGTGTTTCTTTGCTAGGAA	8
-Hairpin14	TACGACTGTGTTGTCCTCTTT	8
-Hairpin15	AACGAAGAATGGGAACCTATA	8
-Hairpin16	CTGCGAGACATCGACCATGAA	9
-Hairpin17	AAGGTGATCCTTATGCTGTTA	9
-Hairpin18	TTCATGCTGCACCAAGATCTA	9
-Hairpin19	CACAGGACAGGTGGACGTCAA	9
-Hairpin20	TACGATCAATAAGACCAGATA	15
-Hairpin21	AGGCTTGGTTGTTTCAATCTA	15
-Hairpin22	TAGGATTGAAGAAGACAAGAA	15
-Hairpin23	ACGATCAATAAGACCAGATAA	15
-Hairpin24	CGGCAAGAAGAAAGTGTGCTA	15
-Hairpin25	TTGCTGCTAAATTATGGTTTA	15
-Hairpin26	TTCTTGCTAGTTACCGATGTA	16
-Hairpin27	CAGATGATGATGTGTATAATA	13
-Hairpin28	TAAGAAGATGATCGTCTTCAA	16
-Hairpin29	ACAGAGACTGTTAGAGATGAA	16
-Hairpin30	CAGAGACTGTTAGAGATGAAA	16
-Hairpin31	TTGCTAGTTACCGATGTATGA	16
-Hairpin32	AACAGATGATGATGTGTATAA	16
-Hairpin33	TGCTATGTCAATGACATAGTA	16
-Hairpin34	GAGATCCAATGTGTTCCTTTA	17
-Hairpin35	ATGCACTCCAGTTGTTCTTAA	17
-Hairpin36	AAGTGTCTGAAGTATGTCCTA	17
-Hairpin37	ATCCAATGTGTTCCTTTAATA	17
-Hairpin38	AGGATGAGAAGTACTATCACA	17
-Hairpin39	TAGCATGGATATGGAGTTAAA	19
-Hairpin40	CTGGATGTCTGTCTTCCGCTA	19
-Hairpin41	CCCCATGCAATTAAAGATATA	19
-Hairpin42	CTGGTATGTCTTGGAGAGATA	20
-Hairpin43	CAGGAATACCAGAGAGAATTA	20
-Hairpin44	TAGGAGAGTTAACCTGTACTA	20
-Hairpin45	AAGGAGCTGAGCAAAGAGCTA	20
-Hairpin46	AACCTGTACTATGTCAGCATA	20
-Hairpin47	CAGAGATACGACGAGAACGAA	20
-Hairpin48	ACCAAGAATCAGGTAGAATAA	20
-Hairpin49	AAGAGGAAGAAGGCAAGTTTA	20
-Hairpin50	AAGAGCAAAGCTGTTCTACAA	24
-Hairpin51	CAGAAGAGCAAAGCTGTTCTA	24
-Hairpin52	TAGCACAAATTGCGAGTCTAA	24
-Hairpin53	ACAGCTGAGATTCCTAAGTTA	24
-Hairpin54	AGGGTGTCTATTTGTCTTCAA	24
-Hairpin55	CAGACTGTGAGGTCAACAATA	24
-Hairpin56	TTCGAGGATGACGACATGTTA	26
-Hairpin57	CTGATTGTTGACAGTGTCAAA	26
-Hairpin58	TCGATGCTATGTTATGTATAA	26
-Hairpin59	AAGGTCGTTAGTTTCTTGTTA	26
-Hairpin60	CAGAAATTATGTGACTATATA	26
-Hairpin61	TGGGACAAGAAGCTAACCAAA	26
-Hairpin62	GAGCTAGATGTGTTCGAGCTA	26
-Hairpin63	CAAGAGGACAAAGGAGGACAA	29
-Hairpin64	TTGCTTATTTCTTCTTTGAAA	29
-Hairpin65	TAGGTTCTGCTCGGACTGCAT	29
-Hairpin66	ACAGATGACTTTGCAGACAAA	32
-Hairpin67	AAAAGCAGTTCTCAAGATCTA	32
-Hairpin68	TGGGTAGACATGACCACTCTA	33
-Hairpin69	CTCAAGATGTCCAGAAGTTCA	32
-Hairpin70	AAGGTCCTTTGTCTATATCAA	35
-Hairpin71	CAGGTGTACAACGTATTCATA	35
-Hairpin72	TGGGTCCACTTGTCTCAGTTA	35
-Hairpin73	AAGGATGACCATCAAATCAGA	35
-Hairpin74	AACTGTGTTGTTGAGTTAATA	35
-Hairpin75	CTGTATGACTTTGAAGTTGAA	35
-Hairpin76	TAGCATTGTTCTCTACAAGAA	36
-Hairpin77	TTGAGAGAAGCTACAGTATTA	36
-Hairpin78	CAGTGTTTGACTGTCTAGATA	36
-Hairpin79	AAGTATGGTTTCATAGATTAA	36
-Hairpin80	CAAGTTGTATGAGAAGGTATA	36
-Hairpin81	AAGGGTCAGAACCCAATGTAA	36
-Hairpin82	CAGAGACAAATAAGTGCTGAA	36
-Hairpin83	GAGGTGGACGACTACAGTCAA	37
-Hairpin84	ACGGACTTAGAGAAACAGATA	37
-Hairpin85	CCAGATGGAGGTGGACGACTA	37
-Hairpin86	CTGAGGCTAATTGTTGGTAAA	37
-Hairpin87	AAGGCTCTGAGAGATATTGAA	37
-Hairpin88	CCGCTACTCCATGGAGACCAA	38
-Hairpin89	AGAGAGCTGATCCTTGTTCTA	38
-Hairpin90	CAGCACTGGAAGCTTTCCTAA	38
-Hairpin91	TTCTATTGATCTGGACATCAA	38
-Hairpin92	AAGAGGATGAAGACCTGCTTA	38
-Hairpin93	CTGCAAGTTTGTGCCCTCAGA	38
-Hairpin94	ATGAGCACTGTGAATGCTATA	38
-Hairpin95	ATGGAAGGAGATCTACTTGAA	22
-Hairpin96	AAGAAGTTTGTTAGCAACATA	5
-Hairpin97	CCGCACTTACTCCAAGTTCAA	5
-Hairpin98	CCCGAAGATCAACTCACCAAA	5
-Hairpin99	CTGGACAATGATGTTCTGTTT	6
-Hairpin100	AGGGTCTATGTTTAAGTCTTA	6
-Hairpin101	AAGGCTCTTCTTCGAGTTTTA	7
-Hairpin102	TAAGTTGTTGCTTACAGAAAA	30
-Hairpin103	CCAGACTTGTTTACACTATTA	30
-Hairpin104	CCTAAGGAAGAGGTGAATGAT	1
-Hairpin105	GCTCTTACTGCTGAGCGTATA	10
-Hairpin106	GCACTTTCATTGAAGAACTAA	11
-Hairpin107	CCAAGCACTGTGGTTGAATAA	39
-Hairpin108	CGAAATCTTATCGCACCAATA	40
-Hairpin109	CTAGTTTGTGTTTGTTTTTAA	27
-Hairpin110	CCACCAAGTTGTAAAGATGTA	27
-Hairpin111	CCCCTGCATCATTGCAACAAA	27
-Hairpin112	TTGGTTTTTGACTATACAAAA	28
-Hairpin113	AGGCAAAATTGTGGATGCTAA	28
-Hairpin114	AGCGTTTGCTGTAAGAAGAAA	23
-Hairpin115	TATGACTGTAATAAAGATAAA	23
-Hairpin116	TAGGTTTTGTTTGCTATCTTA	41
-Hairpin117	TCGTTGAGAGCTCAAAGCTAA	41
-Hairpin118	CAGGTGCAATTGAGAACATTA	3
-Hairpin119	CAGGTCGAAGATCAGAATACA	3
-Hairpin120	CACTACGACACTCTAGTTAAA	34
-Hairpin121	AAGGTTATTCTTCCTGGTTTA	34
-Hairpin122	CTGCAAGAAAAGCATGTCAAA	18
-Hairpin123	CTGGAAATGACTATGATTTAA	18
-Hairpin124	CAAGCTCTTCTAGCAATACTA	18
-Hairpin125	CAGGAGCTTTATCAGACTCTA	21
-Hairpin126	CACGATGAAATGATATGCAAA	21
-Hairpin127	CACAGTGATGACTACATTAAA	14
-Hairpin128	CGCAAGTGCTGTGAAGCTTAA	14
-Hairpin129	AGGGTGTAACTGTGAGATAAA	31
-Hairpin130	CTCACACTCACTCTTAGCTAA	31
-Hairpin131	AACAAGAAAAGCAGTTCTCAA	32
-Hairpin133	CACAGTGAAATCAGTAATTTA	12
-Hairpin134	CTGAACCTTATTCACAGTGAA	12
-Hairpin135	GGGTCTTCCAGCTTTCCTATT	25
--- a/test-data/shrnaseq_zuber_test.html	Mon Jan 19 22:08:26 2015 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,80 +0,0 @@
-<html>
-<head>
-<title>EdgeR Output</title>
-</head>
-<body>
-<h3>EdgeR Analysis Output:</h3>
-<h4>Input Summary:</h4>
-<ul>
-<li>Number of Samples: 4</li>
-<li>Number of Hairpins: 1105</li>
-<li>Number of annotations provided: 1105</li>
-<li>Number of annotations matched to hairpin: 1105</li>
-</ul>
-The estimated common biological coefficient of variation (BCV) is: 0.9323<br />
-No secondary factor specified.<br />
-<h4>Output:</h4>
-PDF copies of JPEGS available in 'Plots' section.<br />
-<img src="barIndex.png" alt="Counts per Index" height="600" width="600"/>
-<img src="barHairpin.png" alt="Counts per Hairpin" height="600" width="600"/>
-<img src="mds.png" alt="MDS Plot" height="600" width="600"/>
-<img src="bcv.png" alt="BCV Plot" height="600" width="600"/>
-<img src="smear(Day.0-Day.14).png" alt="Smear Plot(Day.0-Day.14)" height="600" width="600"/>
-<br />
-<h4>Differential Representation Counts:</h4>
-<table border="1" cellpadding="4">
-<tr>
-<td></td>
-<th>Up</th>
-<th>Flat</th>
-<th>Down</th>
-</tr>
-<tr>
-<th>Day 0-Day 14</th>
-<td>376</td>
-<td>682</td>
-<td>35</td>
-</tr>
-</table><h4>Plots:</h4>
-<a href="barIndex.pdf" target="_blank">Counts per Index Barplot (.pdf)</a><br />
-<a href="barHairpin.pdf" target="_blank">Counts per Hairpin Barplot (.pdf)</a><br />
-<a href="mds.pdf" target="_blank">MDS Plot (.pdf)</a><br />
-<a href="bcv.pdf" target="_blank">BCV Plot (.pdf)</a><br />
-<a href="smear(Day.0-Day.14).pdf" target="_blank">Smear Plot(Day.0-Day.14) (.pdf)</a><br />
-<h4>Tables:</h4>
-<a href="toptag(Day.0-Day.14).tsv" target="_blank">Top Tags Table(Day.0-Day.14) (.tsv)</a><br />
-<a href="counts.tsv" target="_blank">Counts table (.tsv)</a><br />
-<p>Alt-click links to download file.</p>
-<p>Click floppy disc icon on associated history item to download all files.</p>
-<p>.tsv files can be viewed in Excel or any spreadsheet program.</p>
-<h4>Additional Information:</h4>
-<li>Data was gathered from a table of counts.</li>
-<li>Target sequences without more than 0.5 CPM in at least 1 samples are insignificant and filtered out.</li>
-<li>1 of 1094 (0.09%) target sequences were filtered out for low count-per-million.</li>
-<li>Samples that did not produce more than 1000 counts were filtered out.</li>
-<li>0 samples were filtered out for low counts.</li>
-<li>An exact test was performed on each target sequence.</li>
-<h4>Citations</h4><ol>
-<li>Robinson MD, McCarthy DJ and Smyth GK (2010). edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139-140</li>
-<li>Robinson MD and Smyth GK (2007). Moderated statistical tests for assessing differences in tag abundance. Bioinformatics 23, 2881-2887</li>
-<li>Robinson MD and Smyth GK (2008). Small-sample estimation of negative binomial dispersion, with applications to SAGE data. Biostatistics, 9, 321-332</li>
-<li>McCarthy DJ, Chen Y and Smyth GK (2012). Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Research 40, 4288-4297</li>
-</ol>
-<p>Report problems to: su.s@wehi.edu.au</p>
-<a href="session_info.txt" target="_blank">Session Info</a><br />
-<table border="0">
-<tr>
-<td>Task started at:</td>
-<td>2015-01-20 12:16:59</td>
-</tr>
-<tr>
-<td>Task ended at:</td>
-<td>2015-01-20 12:17:05</td>
-</tr>
-<tr>
-<td>Task run time:</td>
-<td>6 secs</td>
-<tr>
-</table>
-</body>
-</html>
\ No newline at end of file
--- a/test-data/zuber-count_matrix.txt	Mon Jan 19 22:08:26 2015 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,1106 +0,0 @@
-ID	Reads_A_T0	Reads_A_T14	Reads_B_T0	Reads_B_T14
-100043305.2	34133	9171	31158	4111
-100043305.4	5589	1	4311	5737
-100043305.5	38651	7722	24711	15331
-2900092E17Rik.377	11759	24	9328	21
-2900092E17Rik.546	3581	30	3211	3
-2900092E17Rik.1051	11498	1907	10809	4116
-2900092E17Rik.1361	5590	1128	5753	1704
-Actl6b.379	8147	3520	8262	3861
-Actl6b.819	7152	5311	7080	2636
-Actl6b.917	3549	3	3326	9
-Actl6b.989	9928	3200	12207	1787
-Actl6b.1221	2449	173	4553	190
-Alkbh2.462	8219	0	8307	3674
-Alkbh2.557	17312	11788	16162	7253
-Alkbh2.590	908	0	3	0
-Alkbh2.640	29881	9982	32507	6981
-Alkbh2.641	30677	31067	21977	5244
-Alkbh3.552	7748	95	10813	628
-Alkbh3.843	7288	47	6161	1141
-Alkbh3.901	11464	10632	13945	986
-Alkbh3.1184	235478	121880	223886	199915
-Aof2.1869	4835	1	6635	18
-Aof2.1956	9168	74	11901	2001
-Aof2.2435	22561	5296	27662	4349
-Aof2.2857	12275	0	13761	0
-Ash1l.1031	40881	12818	35694	11615
-Ash1l.1280	15907	3501	24446	2818
-Ash1l.3810	0	0	570	0
-Ash1l.8132	16135	3240	13553	8157
-Ash1l.9540	19334	4915	19956	482
-Ash2l.586	17315	3908	16296	11351
-Ash2l.805	15308	11745	19785	7504
-Ash2l.948	17154	7175	22222	1182
-Ash2l.1135	10872	23	9514	649
-Ash2l.2130	48820	71306	54356	55586
-Asxl1.2020	8883	85	7366	810
-Asxl1.3548	1499	177	4290	434
-Asxl1.3785	13925	9770	13967	1888
-Asxl1.4792	14695	2973	17368	6663
-Asxl1.5221	207	21	1015	413
-Asxl1.6315	5323	2931	4104	1254
-Asxl2.11	12636	1202	19230	836
-Asxl2.4563	6740	9470	6275	14168
-Asxl2.6593	7040	7865	7327	463
-Asxl2.7130	1005	688	1998	98
-Asxl2.7253	2848	0	4313	1015
-Asxl3.6101	27880	9120	23317	9903
-Asxl3.6824	0	0	0	0
-Asxl3.8947	10505	1283	17111	8040
-Asxl3.10021	11150	77	9094	418
-Asxl3.11070	6878	434	13876	499
-Asxl3.11073	19570	60	23697	1250
-Atm.137	7726	1	7961	0
-Atm.4098	17664	79096	14372	19643
-Atm.4998	5448	0	8348	0
-Atm.5616	26499	17417	25957	5963
-Atm.7782	121694	37584	112860	23911
-Atm.9396	23098	8301	16153	13589
-Atr.1239	7318	0	7499	76
-Atr.3160	4630	0	2454	0
-Atr.4762	7087	502	6196	1408
-Atr.6186	14186	1517	14242	2136
-Atr.7888	2705	715	1274	40
-Atrx.2490	21802	13082	20344	3929
-Atrx.5490	9146	4876	8110	1459
-Atrx.6144	22072	50037	17635	135473
-Atrx.7173	20760	2010	32941	360
-Atrx.7377	4661	7127	5894	858
-Aurkb.520	10448	158	8464	14
-Aurkb.631	12294	13088	16774	9788
-Aurkb.917	9721	85	7381	297
-Aurkb.928	3823	0	3360	70
-Aurkb.1620	2783	0	1689	0
-Aurkb.1803	5485	964	6727	502
-Baz1a.2095	17890	6381	16476	10861
-Baz1a.2451	8018	26337	7113	7350
-Baz1a.4993	4040	2049	5627	4388
-Baz1a.5946	8518	471	7167	756
-Baz1b.801	3377	3	2560	1
-Baz1b.3683	19598	1361	14007	9115
-Baz1b.5646	7619	140	6540	93
-Baz1b.6371	20503	0	14675	4199
-Bmi1.698	13315	927	12090	1400
-Bmi1.895	22321	1589	22783	0
-Bmi1.1440	148	0	1337	0
-Bmi1.1746	57319	7041	58914	6748
-Bmi1.2404	2012	0	5750	0
-Bmi1.2561	7381	4663	6301	1752
-Bop1.778	22193	9880	25011	22498
-Bop1.2228	9126	1164	11243	1759
-Bop1.2403	1267	0	2340	0
-Bptf.1622	19917	1645	16672	1194
-Bptf.3234	29927	1975	29930	1459
-Bptf.7211	9162	196	8435	235
-Bptf.8224	22786	4089	25881	16627
-Braf.3750	251680	111577	252403	96275
-Braf.3826	36692	6171	38833	3552
-Braf.5053	21572	58690	24272	47962
-Brd1.286	2667	1	3889	732
-Brd1.287	47567	32364	42739	11998
-Brd1.2096	15510	483	12893	662
-Brd1.4229	1776	47	2985	0
-Brd2.813	8544	364547	19761	57153
-Brd2.1714	7605	1900	7256	279
-Brd2.3011	1335	40	1645	44
-Brd2.3396	447	431	1478	90
-Brd3.187	20291	0	16080	1
-Brd3.298	45100	2627	41908	2295
-Brd3.411	3322	4993	9122	88
-Brd3.4162	4380	3233	4235	2236
-Brd4.523	59871	250	62100	1030
-Brd4.552	4366	0	4085	0
-Brd4.632	6519	0	8625	0
-Brd4.1448	18590	2201	13467	2049
-Brd4.2097	15250	0	12300	0
-Carm1.892	7893	3	7502	1189
-Carm1.1222	6127	0	5712	860
-Carm1.1454	6356	0	4529	0
-Carm1.1614	2578	0	2116	1032
-Carm1.1717	10432	26	5147	5
-Cbx1.1004	2119	176	2118	68
-Cbx1.1053	55760	32885	49270	78522
-Cbx1.1099	6839	6288	10338	2367
-Cbx1.1103	16450	2350	10274	7958
-Cbx1.1210	4161	1553	6473	768
-Cbx2.2033	3805	6	3394	910
-Cbx2.3537	1236	0	1822	0
-Cbx2.3545	1510	1926	1608	235
-Cbx2.3620	4720	41	4982	1298
-Cbx2.3706	15664	23374	12341	9903
-Cbx3.882	3121	0	3119	0
-Cbx3.1206	13461	1774	17078	1812
-Cbx3.1339	19195	1352	22424	4795
-Cbx3.1719	4977	0	5860	0
-Cbx3.1735	20825	237	16087	3528
-Cbx4.1794	9233	3426	6939	16366
-Cbx4.1844	2832	3464	4193	744
-Cbx4.2573	69888	62259	67617	50333
-Cbx4.4403	3806	0	4281	1847
-Cbx4.5120	11707	4670	9880	5888
-Cbx5.1309	20635	20130	21845	21774
-Cbx5.4366	907	0	563	0
-Cbx5.4409	9565	1475	14591	3062
-Cbx5.4508	26823	20517	26002	16192
-Cbx5.5707	3839	488	2459	831
-Cbx5.8586	2634	924	4578	8
-Cbx6.1535	1684	44	2014	5254
-Cbx6.3332	32724	36460	41754	5931
-Cbx6.3473	1027	199	1093	2766
-Cbx6.3969	25243	20256	20037	7607
-Cbx7.745	41390	8417	44824	10473
-Cbx7.1633	9110	0	7318	594
-Cbx7.1634	8492	1	7765	1175
-Cbx7.1639	3050	380	4027	305
-Cbx7.2006	12881	0	11203	1803
-Cbx7.2504	15650	74	14065	1023
-Cbx8.136	14429	562	10096	1833
-Cbx8.1120	23518	5129	18818	4414
-Cbx8.1342	91120	117507	88227	77242
-Chaf1a.166	7650	0	8656	0
-Chaf1a.1039	1166	0	1879	0
-Chaf1a.2122	36245	25317	42693	4155
-Chaf1b.367	1271	0	3122	0
-Chaf1b.566	5644	2726	6501	805
-Chaf1b.692	8344	4791	14305	0
-Chaf1b.901	11840	1680	10452	2885
-Chaf1b.1223	3527	0	4039	327
-Chd1.746	42149	4740	47141	5029
-Chd1.1103	9539	301	10681	317
-Chd1.2443	9033	998	8891	1151
-Chd1.2959	17519	3663	17844	3550
-Chd1.4558	16095	18060	18409	694
-Chd1l.2305	13833	2232	9271	1687
-Chd1l.2598	2003	4	3653	467
-Chd1l.2804	8186	1848	9889	4110
-Chd2.926	12754	2298	14491	1390
-Chd2.3700	18791	8160	17139	6180
-Chd2.3984	39660	3183	28160	5299
-Chd2.8087	21625	5699	19522	2258
-Chd2.8913	44266	4697	48691	2032
-Chd3.482	5654	84	2967	437
-Chd3.3249	18194	209	16629	2181
-Chd3.4011	12016	5122	15608	2384
-Chd3.6496	8188	250	11414	658
-Chd3.7148	6057	11694	5216	14343
-Chd3.7149	18779	2183	20787	4073
-Chd4.2060	3613	0	9449	3
-Chd4.3326	0	0	0	0
-Chd4.3423	18147	329	24617	1474
-Chd4.3772	18305	1967	17413	13691
-Chd5.2301	20061	34429	23079	1480
-Chd5.2900	8518	12121	8113	23821
-Chd5.5471	16812	135	14891	832
-Chd5.6392	27664	42408	24064	32029
-Chd6.311	5183	30	4482	283
-Chd6.4698	11850	691	9494	952
-Chd6.4988	9782	9443	8227	3677
-Chd6.9610	4646	4252	7143	2341
-Chd7.1269	5308	36016	5596	15544
-Chd7.1502	17568	19902	24339	10329
-Chd7.5857	24131	42321	23035	13811
-Chd7.6498	2585	2388	3680	681
-Chd7.7229	4726	3715	3325	5096
-Chd8.434	10501	5059	13580	0
-Chd8.3265	14017	45094	15274	35713
-Chd8.4169	46755	130786	47380	90425
-Chd8.5352	15081	0	10249	963
-Chd8.6946	24933	3532	29506	678
-Chd9.1402	8846	10701	5390	15209
-Chd9.3919	30650	5485	31316	8951
-Chd9.9352	4541	7	4353	547
-Chd9.10928	11786	846	6533	3211
-Clock.693	30386	192421	30632	61226
-Clock.1387	3512	16	6185	1879
-Clock.4461	8821	15720	13658	32530
-Clock.4611	7531	1868	7634	960
-Clock.5863	8924	0	6154	0
-Crebbp.704	6954	132149	5748	28129
-Crebbp.2064	15054	21613	9232	8683
-Crebbp.2118	16858	416	14067	1155
-Crebbp.3582	10871	49874	11472	31243
-Crebbp.4463	10735	244297	8756	87465
-Ctsl.940	64046	40415	67042	33661
-Ctsl.1445	4304	11403	6955	921
-Ctsl.1941	14957	114	9881	1230
-Ctsl.1942	3801	651	5404	119
-Ctsl.1947	83104	55376	79952	45160
-Cxxc1.68	22254	7624	21861	13433
-Cxxc1.359	16364	0	14694	712
-Cxxc1.1889	13048	105	15103	1803
-Cxxc1.2034	10733	2431	11257	5220
-Cxxc1.2133	24632	4890	18850	3756
-Dmap1.439	22069	17051	18179	11546
-Dmap1.518	270	6	835	0
-Dmap1.1354	27540	2702	27126	5348
-Dmap1.1355	38236	3410	25053	19190
-Dmap1.1487	16458	35264	12204	7974
-Dnmt1.437	2774	1	4466	1933
-Dnmt1.828	37302	0	37771	2350
-Dnmt1.1137	1982	0	900	0
-Dnmt1.4462	19205	1622	19314	2525
-Dnmt1.4848	11770	53612	13284	12279
-Dnmt3a.16	28736	52935	39231	63096
-Dnmt3a.1669	7497	2055	9359	279
-Dnmt3a.2338	26093	14264	21886	8356
-Dnmt3a.4173	90754	147980	91811	371738
-Dnmt3b.275	2759	0	4350	967
-Dnmt3b.579	23800	2457	15840	4413
-Dnmt3b.958	18118	1831	14535	41
-Dnmt3b.2218	4817	0	5321	0
-Dnmt3l.306	1360	0	7206	133
-Dnmt3l.760	107789	89964	109791	48867
-Dnmt3l.1049	12911	3759	16355	4238
-Dnmt3l.1333	10696	5884	9512	8646
-Dnmt3l.1350	11998	13780	13122	7740
-Dot1l.602	15468	1611	18782	28
-Dot1l.941	308	0	1	0
-Dot1l.3626	1819	0	2461	0
-Dub2a.769	20173	45614	27227	22193
-Dub2a.1334	3322	913	3054	1061
-Dub2a.1391	7400	0	6144	0
-Dub2a.1397	1989	1475	2177	2420
-Dub2a.1444	6000	772	9736	1277
-Dub2a.1445	17909	5522	13925	4446
-Edf1.486	21827	12951	27904	16057
-Edf1.628	14218	14904	9199	1968
-Edf1.631	17016	5000	14264	1849
-Edf1.652	14581	2743	14121	1112
-Eed.710	5375	0	4431	0
-Eed.949	19036	15171	17602	11188
-Eed.1083	40824	1687	39480	698
-Eed.1397	27933	4138	25394	8774
-Eed.1820	36795	99609	29844	5995
-EG330129.869	2661	61	1902	619
-EG330129.2118	14758	1039	18080	5314
-EG330129.2262	15426	19116	20410	28859
-EG330129.2329	19693	6224	15507	1799
-EG546387.1344	61423	132971	65502	105110
-EG546387.2159	18532	5441	17522	6441
-EG546387.2272	5181	2230	3858	1293
-Ehmt1.66	23038	3862	34576	8831
-Ehmt1.386	78913	8990	88361	18872
-Ehmt1.859	3728	0	2265	0
-Ehmt1.920	12674	47588	15786	8109
-Ehmt1.3003	17009	4	13764	0
-Ehmt2.724	28567	15002	19363	7218
-Ehmt2.1880	16161	724	10956	2142
-Ehmt2.2014	9586	2303	10876	5893
-Ehmt2.3146	20606	4947	20381	4673
-Ehmt2.3202	12157	924	12076	0
-Elp3.117	13584	1649	11794	7368
-Elp3.215	14727	1372	14790	23
-Elp3.219	17103	125	19102	1933
-Elp3.592	7651	1	13554	437
-Ep300.754	49982	34746	48931	26824
-Ep300.3850	4229	0	4817	0
-Ep300.5490	19810	2485	18297	1698
-Ep300.7826	25198	3046	25177	307
-Ep300.8647	34570	13119	36600	5763
-Evi1.649	23821	1022	23583	938
-Evi1.652	4938	1433	6371	7108
-Evi1.1371	6351	4198	5211	3390
-Evi1.1978	0	0	0	0
-Evi1.2720	8079	4150	7301	4240
-Ezh1.68	23617	6527	29619	30045
-Ezh1.73	2152	1	2857	3113
-Ezh1.4104	5575	74	3572	1105
-Ezh1.4105	10809	0	9427	3236
-Ezh2.556	5195	3183	2808	898
-Ezh2.1370	13095	1	16542	4081
-Ezh2.1678	39634	33392	36467	37036
-Ezh2.2124	24614	13542	24923	1861
-Ezh2.2253	23466	844	25517	49
-Fbxl10.356	9135	6792	12154	10033
-Fbxl10.443	1186	0	1217	0
-Fbxl10.3131	12157	3918	15296	5301
-Fbxl10.3145	28882	145367	25071	266575
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-Prdm1.862	13674	1272	17495	2820
-Prdm1.919	7981	211	6452	659
-Prdm1.2964	9702	1649	6519	74
-Prdm1.3709	6880	2963	4367	6545
-Prdm10.318	38326	1624	35774	3435
-Prdm10.1130	22199	3710	18678	2910
-Prdm10.1348	14385	2569	11194	719
-Prdm10.2613	9338	5136	8248	0
-Prdm11.1844	7683	26	9378	903
-Prdm11.2306	2693	505	1394	36
-Prdm11.3215	34411	12308	45331	6294
-Prdm11.3216	9073	928	6858	1530
-Prdm12.481	11080	1	8398	2032
-Prdm12.603	18533	2716	14848	1285
-Prdm12.1421	11165	13	7190	522
-Prdm12.2351	35983	35549	39030	28743
-Prdm13.554	6553	145	6306	626
-Prdm13.2613	24026	74465	26691	198619
-Prdm13.2702	1483	0	964	1006
-Prdm13.2828	21409	2400	19712	753
-Prdm13.2936	20674	4192	24072	8085
-Prdm14.530	6054	2386	6453	2689
-Prdm14.1756	2872	0	3280	39
-Prdm14.1934	1736	915	2137	128
-Prdm14.2271	23286	2272	18192	2265
-Prdm14.2348	4410	186	4574	4312
-Prdm15.958	948	1832	1351	44
-Prdm15.1034	7500	28	7058	31
-Prdm15.1690	11098	4766	8877	5507
-Prdm15.1796	18603	3415	17010	2809
-Prdm15.2734	6593	26	11491	850
-Prdm16.680	27382	18093	23775	9678
-Prdm16.5683	9804	1774	12654	158
-Prdm16.8212	510	0	75	0
-Prdm16.8363	32959	8200	37005	22671
-Prdm16.8571	41183	105040	34452	72617
-Prdm2.1020	5835	1513	6535	313
-Prdm2.4191	17204	8644	12039	7427
-Prdm2.4655	0	0	0	0
-Prdm2.4956	30817	4934	19758	407
-Prdm2.5781	7580	2678	7412	1599
-Prdm4.1943	32986	1564	27413	5021
-Prdm4.2535	5176	1	4929	841
-Prdm4.3139	3980	0	1329	3
-Prdm4.3391	12217	729	13747	1087
-Prdm4.3667	189	0	71	0
-Prdm5.908	17017	2184	16584	2824
-Prdm5.984	9047	5630	6870	1405
-Prdm5.1353	5507	11532	2450	2925
-Prdm5.2148	29180	20887	26070	15137
-Prdm6.1018	8513	95	9250	75
-Prdm6.1790	27811	2748	38933	5747
-Prdm6.1823	10397	3921	13953	3896
-Prdm6.1839	8440	2848	8331	542
-Prdm8.2290	2074	1	1661	1
-Prdm8.3042	18563	110944	22244	10919
-Prdm8.3048	9249	10791	8032	922
-Prdm8.3062	34157	8769	24864	11608
-Prdm9.77	8384	2377	9245	4796
-Prdm9.496	2638	207	1667	611
-Prdm9.1838	28476	11399	32679	6714
-Prkaa1.145	15289	2584	16946	1937
-Prkaa1.1981	7523	146	8342	164
-Prkaa1.3080	1662	0	458	0
-Prkaa1.3635	51745	221378	47732	100294
-Prkaa1.3954	3718	0	3379	89
-Prkaa1.4596	14178	836	18454	170
-Prkaa2.2299	2066	1	4279	35
-Prkaa2.2748	1877	680	1923	614
-Prkaa2.4825	0	0	21	0
-Prkaa2.6172	2701	0	2936	119
-Prkaa2.6849	21406	1548	23709	4690
-Prkcd.161	5086	508	6961	1803
-Prkcd.441	685	1	1449	947
-Prkcd.707	9014	9663	10168	2609
-Prkcd.1389	1525	978	1423	2661
-Prmt1.243	15068	1812	18422	1862
-Prmt1.264	46040	17605	55341	9030
-Prmt1.630	20371	35935	26429	23619
-Prmt1.1014	26740	17066	25371	8374
-Prmt2.151	7523	284	7173	183
-Prmt2.154	8667	10496	12546	9225
-Prmt2.1066	5444	1	4843	0
-Prmt2.1067	11455	7496	10344	10105
-Prmt3.502	2673	842	4409	0
-Prmt3.814	7852	0	10218	1
-Prmt3.838	26818	112940	29743	86471
-Prmt3.985	43276	18317	37898	4768
-Prmt3.1839	2270	338	6325	498
-Prmt5.56	1674	759	613	677
-Prmt5.266	40637	7070	40157	9218
-Prmt5.2152	5093	390	7676	1360
-Prmt5.2293	8377	3933	8176	31947
-Prmt6.247	16408	14	12340	822
-Prmt6.1493	4884	1134	4611	168
-Prmt6.1983	10376	1738	7729	1099
-Prmt6.2355	7539	4086	9278	4263
-Prmt7.23	1245	6	1139	16
-Prmt7.45	41811	21691	44665	25418
-Prmt7.88	21561	1050	22146	2492
-Prmt7.1284	11267	1422	12595	48
-Prmt7.2135	13417	5187	13065	1089
-Prmt8.302	32365	6417	32121	9345
-Prmt8.455	29562	23733	30364	11859
-Prmt8.667	9965	870	10199	41
-Prmt8.1854	35676	2488	32704	4795
-Psip1.763	4282	0	4395	73
-Psip1.1311	2929	0	7223	0
-Psip1.1596	24286	2117	24019	775
-Psip1.2474	10661	133	13615	0
-Psip1.2652	54657	5848	56080	947
-Rbbp4.2088	14907	1879	17367	4542
-Rbbp4.2174	2162	0	1290	15
-Rbbp4.2511	23749	23858	32454	27646
-Rbbp4.3753	8597	1167	6013	66
-Rbbp5.1634	33001	38166	28644	25077
-Rbbp5.2248	29504	43	32701	4
-Rbbp5.2655	6168	1052	11246	825
-Rbbp5.2974	7237	10464	10292	13922
-Renilla.713	367178	563164	344553	620131
-Ring1.260	1691	45	1582	863
-Ring1.669	11819	2018	8157	1301
-Ring1.1034	4600	75	7179	2477
-Rnf2.1856	7494	6249	13866	7112
-Rnf2.2203	30535	25972	25569	27068
-Rnf2.2538	46115	24976	46018	52199
-Rnf2.2809	9879	810	8811	2579
-Rnf2.2875	37646	26066	40057	16086
-Rnf20.420	36503	1984	34359	2525
-Rnf20.948	33597	14226	54979	7373
-Rnf20.1295	4427	0	4587	1
-Rnf20.3244	0	0	0	0
-Rnf20.3277	41281	33163	38179	4449
-Rnf20.3718	12555	17757	8721	7494
-Rpa1.1620	45458	16	57357	807
-Rpa3.276	35854	4	28720	1
-Rpa3.455	66725	1381	54371	851
-Rpa3.561	208162	536	199970	1389
-Satb1.710	5263	1702	7524	4
-Satb1.1401	36326	12944	26886	11529
-Satb1.1478	4562	2161	5968	38
-Satb1.1709	14269	1071	12405	3873
-Satb1.2566	3710	131	1155	407
-Setd1a.119	4384	748	4155	184
-Setd1a.388	33695	22014	30190	17010
-Setd1a.643	38998	65977	44426	60023
-Setd1a.5859	12239	11023	14509	10084
-Setd1b.3553	11381	0	18226	3
-Setd1b.3557	10915	1966	9020	1635
-Setd1b.4520	20976	1076	17850	6222
-Setd1b.4522	5428	0	10172	68
-Setd1b.4699	29600	2899	29677	5249
-Setd2.182	50766	2411	51817	1703
-Setd2.1467	7627	0	8664	3
-Setd2.1785	19426	534	23462	1152
-Setd2.3632	15881	7077	15278	4722
-Setd2.4051	8105	0	9809	0
-Setd3.795	3477	95	4288	970
-Setd3.1496	424	0	150	0
-Setd3.2395	5170	0	7159	175
-Setd4.506	8915	16	7889	13
-Setd4.1308	19600	1	30802	0
-Setd4.1517	2249	0	1736	0
-Setd7.4328	27912	38276	31452	6959
-Setd7.5317	23119	13552	19804	5863
-Setd7.5342	29195	1276	25869	6316
-Setd7.5940	0	0	0	0
-Setd7.7009	40400	1995	34707	2878
-Setd8.2578	4113	4	3366	1274
-Setd8.2622	42611	26560	45421	9076
-Setd8.2632	86958	216794	99707	79091
-Setdb1.1145	22800	10730	18391	10380
-Setdb1.1925	19087	0	12578	2178
-Setdb1.2174	9258	1	6981	2039
-Setdb1.3684	11551	1	13226	274
-Setdb2.809	10440	29022	8305	21
-Setdb2.810	37568	36190	41634	58990
-Setdb2.990	28467	613	24673	3385
-Setdb2.1417	9056	3565	14238	4287
-Setmar.1193	18271	6544	15427	3510
-Setmar.1195	9944	1350	9967	1878
-Setmar.1589	23950	1248927	26938	2049408
-Sfmbt1.868	7566	9131	8793	7208
-Sfmbt1.1345	9354	98	8211	55
-Sfmbt1.1802	3435	2478	2641	3402
-Sfmbt1.2018	2922	1389	1521	90
-Sfmbt1.2421	14771	24	12907	1929
-Sfmbt2.602	14404	7493	12974	547
-Sfmbt2.3592	7795	44	3204	513
-Sfmbt2.5673	10825	213	8582	2138
-Sin3a.531	634	0	1702	0
-Sin3a.3537	22343	0	23130	1126
-Sin3a.3559	3950	11186	4588	2872
-Sin3a.4729	2903	0	3390	0
-Sin3b.188	6644	562	7276	0
-Sin3b.326	40114	91267	52170	31420
-Sin3b.338	6940	0	4025	850
-Sin3b.381	3401	844	1798	39
-Sin3b.475	4577	5120	5887	945
-Sirt1.688	19362	38333	23363	21555
-Sirt1.1708	197153	144560	193622	102444
-Sirt1.1779	17885	6024	15615	8384
-Sirt1.2191	7851	19851	6431	5987
-Sirt2.735	10121	31	8695	2542
-Sirt2.1418	51603	4818	41566	7049
-Sirt2.1460	9317	2705	4885	1287
-Sirt2.1600	28368	738	27560	591
-Sirt3.462	12608	8937	23079	3496
-Sirt3.869	7400	241	6738	958
-Sirt3.993	8931	9252	7877	9460
-Sirt3.1002	2040	426	2568	1087
-Sirt3.1236	15566	3873	20108	4350
-Sirt4.105	28968	24512	24897	18143
-Sirt4.633	14159	257	11725	9490
-Sirt4.1490	7280	3400	12576	961
-Sirt4.1806	21710	7905	25165	1464
-Sirt5.586	41392	2529	43804	1104
-Sirt5.1032	981	0	444	671
-Sirt5.1219	43332	63257	35460	30451
-Sirt5.1290	14394	2383	24051	3183
-Sirt6.83	24755	1313	21310	405
-Sirt6.421	14293	0	12196	3
-Sirt6.937	17858	2868	28828	8748
-Sirt6.1609	18792	1621	18577	11944
-Sirt7.841	2362	0	2342	0
-Sirt7.844	30249	3373	28104	9318
-Sirt7.1238	14603	3027	8531	1909
-Sirt7.1604	3339	13	3293	767
-Sirt7.1677	8411	4502	6020	2215
-Smarca1.1401	33840	57146	25759	15929
-Smarca1.1430	29317	23044	26964	3632
-Smarca1.1613	26153	1619	25359	4043
-Smarca1.1893	15155	3318	11343	2367
-Smarca1.3418	18683	20393	21196	2633
-Smarca2.263	28313	5055	19538	3254
-Smarca2.274	799	0	685	0
-Smarca2.712	3352	13	4803	323
-Smarca2.1061	18983	2278	7875	323
-Smarca4.3232	1287	0	1543	0
-Smarca4.3364	12192	0	9172	3410
-Smarca4.3633	12283	2082	7827	268
-Smarca4.4935	20721	13230	19425	5625
-Smarca4.5466	2050	0	1324	0
-Smarca5.1139	38415	1132532	46081	2237665
-Smarca5.1264	11896	1222	13262	0
-Smarca5.3886	10888	46556	5016	7539
-Smarca5.4421	1718	81	4763	33
-Smarca5.4522	10483	13647	10095	20371
-Smarcc2.1398	29247	234724	29717	98347
-Smarcc2.1941	4410	553	7885	9608
-Smarcc2.2235	15214	6310	16647	2339
-Smarcc2.2541	15431	6136	13795	4700
-Smarcd1.690	13166	129	15195	758
-Smarcd1.986	14993	3694	16328	724
-Smarcd1.1738	8832	11477	8520	1934
-Smarcd1.1858	10888	3275	9600	888
-Smarcd3.518	12413	2339	11321	342
-Smarcd3.847	26274	4645	19349	7316
-Smarcd3.1323	28661	13110	28557	6669
-Smarcd3.1591	4047	935	3632	15
-Smarcd3.1708	2642	0	8094	0
-Smarce1.2096	9533	1983	6689	1627
-Smarce1.2121	36774	145025	36347	291079
-Smarce1.2154	29474	1127	40937	12039
-Smarce1.2337	28357	12960	30056	20823
-Smarce1.2593	11618	786	9889	1345
-Smyd1.1302	18136	2610	24378	2014
-Smyd1.1635	22181	16847	24576	23009
-Smyd1.1658	1744	139	1322	1184
-Smyd2.334	6201	2644	8081	1941
-Smyd2.640	4778	0	8728	0
-Smyd2.1421	5873	43	8087	485
-Smyd2.1476	29280	4886	27735	2780
-Smyd3.306	36640	64693	27190	5504
-Smyd3.438	7299	2499	7015	1359
-Smyd3.980	7252	51716	12288	65481
-Smyd3.1506	11477	0	9246	0
-Smyd3.2607	20309	10800	20516	5798
-Smyd4.693	7240	0	6185	429
-Smyd4.2959	10105	1792	11907	850
-Smyd4.3333	23476	3958	24531	9662
-Smyd4.3414	9832	633	10665	83
-Smyd4.3439	24075	2841	30616	2676
-Smyd5.1548	3233	3575	2919	14
-Smyd5.1643	22979	5462	25329	4173
-Smyd5.2044	4110	0	5406	1087
-Smyd5.2048	32582	187333	27131	88007
-Srcap.2697	2734	0	4412	3083
-Srcap.3130	26303	6435	28044	5059
-Srcap.5342	25111	1863	34202	1023
-Srcap.7360	2702	1	2989	0
-Srcap.11381	33874	12408	23101	5718
-Ssrp1.306	9024	0	5331	1396
-Ssrp1.577	11830	0	10214	0
-Ssrp1.897	1979	0	1920	0
-Ssrp1.975	9139	0	5141	1787
-Ssrp1.2237	18404	9074	12412	6693
-Supt16h.1672	19141	0	16741	0
-Supt16h.2037	3987	0	5301	0
-Supt16h.2827	2799	0	3742	1904
-Supt16h.2999	7017	13525	9120	10585
-Suv39h1.496	9760	51	9748	99
-Suv39h1.1016	11061	2285	8960	1041
-Suv39h1.1202	9865	18	9681	8563
-Suv39h1.1471	37679	28758	31264	26986
-Suv39h1.1827	8924	0	8966	26
-Suv39h2.1395	11929	19031	17833	17100
-Suv39h2.1871	14656	12220	13167	18556
-Suv39h2.2981	45343	27039	52720	14100
-Suv39h2.4184	35743	5240	31412	6431
-Suv420h1.1112	38281	18821	28569	15950
-Suv420h1.1327	3903	0	5390	1259
-Suv420h1.3263	15175	7482	15676	3830
-Suv420h1.3357	6838	14010	10166	6097
-Suv420h2.287	4714	35	1766	68
-Suv420h2.686	12691	1372	12522	1533
-Suv420h2.825	3954	0	4272	15
-Suz12.909	19186	788	22747	876
-Suz12.1676	48602	41328	42913	5210
-Suz12.1842	20807	0	26947	0
-Suz12.3979	34551	25839	37312	26473
-Suz12.4300	95918	361295	105525	82284
-Taf1.928	29566	17762	30431	7446
-Taf1.3994	3805	11349	4811	10913
-Taf1.5030	16687	97640	11553	1419722
-Taf1.7786	26447	3893	17078	15382
-Taf3.1009	47005	40334	56864	22863
-Taf3.1315	9721	1	11094	5798
-Taf3.1769	7972	348	4563	2535
-Taf3.2951	2050	0	3001	0
-Taf3.3182	2441	4367	7877	4886
-Ube2a.142	6844	0	10490	0
-Ube2a.786	26843	3732	31512	3188
-Ube2a.1206	16679	1913	13264	2325
-Ube2a.1411	12770	1093	15872	551
-Ube2b.776	11624	596	15283	991
-Ube2b.1626	5770	228	4749	460
-Ube2b.1661	11131	10339	15579	1101
-Ube2b.2075	36359	11211	35981	12669
-Ube2b.2079	27519	36285	22274	73852
-Ube2e1.228	9870	580	7343	0
-Ube2e1.858	44362	142918	47668	36510
-Ube2e1.1041	27358	51197	25570	21613
-Ube2e1.1126	7564	45	9319	711
-Ube2e1.1207	17571	12619	15690	7099
-Ube2e1.1357	64966	13745	77653	28390
-Ube2i.40	2401	1010	2600	1494
-Ube2i.2212	62796	63531	58362	90071
-Ube2i.2447	6276	607	7252	0
-Ube2i.2498	51201	35736	51072	80735
-Usp22.1429	13262	5695	17290	9139
-Usp22.2382	31385	3450	32459	3697
-Usp22.2760	8601	267	5822	541
-Usp22.3603	1065	1	273	0
-Usp27x.1408	3564	45	4275	997
-Usp27x.2829	25035	4402	24751	8224
-Usp27x.2922	2730	1290	3453	578
-Usp27x.3592	6464	341	5536	2973
-Usp27x.3593	14001	3741	11248	384504
-Usp51.737	1039	406	562	802
-Usp51.1997	53674	23257	51654	9694
-Usp51.2109	7975	1484	8900	1269
-Usp51.2114	12165	116	13434	917
-Usp51.2194	3678	724	1318	2196
-Utx.652	13068	56560	19451	96391
-Utx.888	18640	32639	23825	9547
-Utx.1445	17137	32295	23244	29207
-Utx.4317	33766	102551	27815	12107
-Utx.4510	12851	40012	12155	17742
-Wbp7.2972	24413	60018	36070	20515
-Wbp7.3029	8164	0	11414	806
-Wbp7.5587	1840	0	2933	0
-Wbp7.6965	2142	0	1208	0
-Wdr5.501	9132	40067	12091	5193
-Wdr5.502	7780	475	6238	144
-Wdr5.1321	33084	8610	29142	6825
-Wdr5.1765	15206	0	11812	0
-Wdr5.2837	10752	1577	8922	76
-Wdr82.1889	9318	158922	6926	133595
-Wdr82.3590	102793	67621	100194	42465
-Wdr82.3705	25607	2390	22211	5706
-Wdr82.4023	47467	54245	35961	10951
-Whsc1.812	5301	8373	8384	1919
-Whsc1.818	21079	7170	18333	11013
-Whsc1.3055	20202	3	16818	4080
-Whsc1.3056	14848	3566	17067	3063
-Whsc1l1.276	8983	16	15356	86
-Whsc1l1.373	24335	1	18394	19
-Whsc1l1.524	25667	33492	20530	18722
-Whsc1l1.1307	36165	3810	43502	5067
-Whsc1l1.1653	1740	0	2619	0
-Wnt5a.2013	14662	2054	14921	8784
-Wnt5a.2659	31981	25084	30296	21463
-Wnt5a.2764	3508	402	4188	0
-Wnt5a.4154	24598	41766	25258	11415
--- a/test-data/zuber-sample_anno.txt	Mon Jan 19 22:08:26 2015 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,5 +0,0 @@
-"ID"	"group"
-"Reads_A_T0"	"Day 0"
-"Reads_A_T14"	"Day 14"
-"Reads_B_T0"	"Day 0"
-"Reads_B_T14"	"Day 14"
--- a/test-data/zuber-target_anno.txt	Mon Jan 19 22:08:26 2015 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,1106 +0,0 @@
-ID	Gene	GeneID	Pool	shRNA_start	Mean_T14.T0	T14.T0_A	T14.T0_B
-100043305.2	100043305	100043305	LIB	158	0.200312349	0.268684264	0.131940433
-100043305.4	100043305	100043305	LIB	369	0.665480322	0.000178923	1.330781721
-100043305.5	100043305	100043305	LIB	458	0.410099904	0.199787845	0.620411962
-2900092E17Rik.377	2900092E17Rik	67278	LIB	377	0.002146138	0.00204099	0.002251286
-2900092E17Rik.546	2900092E17Rik	67278	LIB	546	0.004655918	0.008377548	0.000934288
-2900092E17Rik.1051	2900092E17Rik	67278	LIB	1051	0.273324357	0.165854931	0.380793783
-2900092E17Rik.1361	2900092E17Rik	67278	LIB	1361	0.2489911	0.201788909	0.29619329
-Actl6b.379	Actl6b	83766	LIB	379	0.449690571	0.432060881	0.467320261
-Actl6b.819	Actl6b	83766	LIB	819	0.557452935	0.742589485	0.372316384
-Actl6b.917	Actl6b	83766	LIB	917	0.001775631	0.000845309	0.002705953
-Actl6b.989	Actl6b	83766	LIB	989	0.234356062	0.322320709	0.146391415
-Actl6b.1221	Actl6b	83766	LIB	1221	0.056185902	0.070641078	0.041730727
-Alkbh2.462	Alkbh2	231642	LIB	462	0.221138799	0	0.442277597
-Alkbh2.557	Alkbh2	231642	LIB	557	0.564841845	0.680914972	0.448768717
-Alkbh2.590	Alkbh2	231642	LIB	590	NA	NA	NA
-Alkbh2.640	Alkbh2	231642	LIB	640	0.274406089	0.334058432	0.214753745
-Alkbh2.641	Alkbh2	231642	LIB	641	0.625663102	1.012713108	0.238613096
-Alkbh3.552	Alkbh3	69113	LIB	552	0.035169734	0.012261229	0.058078239
-Alkbh3.843	Alkbh3	69113	LIB	843	0.095823083	0.006448957	0.185197208
-Alkbh3.901	Alkbh3	69113	LIB	901	0.499065664	0.927424983	0.070706346
-Alkbh3.1184	Alkbh3	69113	LIB	1184	0.705258812	0.517585507	0.892932117
-Aof2.1869	Aof2	99982	LIB	1869	0.001459856	0.000206825	0.002712886
-Aof2.1956	Aof2	99982	LIB	1956	0.088104342	0.008071553	0.168137131
-Aof2.2435	Aof2	99982	LIB	2435	0.195980329	0.234741368	0.15721929
-Aof2.2857	Aof2	99982	LIB	2857	0	0	0
-Ash1l.1031	Ash1l	192195	LIB	1031	0.31947451	0.313544189	0.32540483
-Ash1l.1280	Ash1l	192195	LIB	1280	0.167683133	0.220091783	0.115274483
-Ash1l.3810	Ash1l	192195	LIB	3810	NA	NA	NA
-Ash1l.8132	Ash1l	192195	LIB	8132	0.401332534	0.200805702	0.601859367
-Ash1l.9540	Ash1l	192195	LIB	9540	0.139184254	0.254215372	0.024153137
-Ash2l.586	Ash2l	23808	LIB	586	0.46112578	0.22570026	0.696551301
-Ash2l.805	Ash2l	23808	LIB	805	0.573261557	0.767245885	0.37927723
-Ash2l.948	Ash2l	23808	LIB	948	0.235730162	0.418269791	0.053190532
-Ash2l.1135	Ash2l	23808	LIB	1135	0.035165394	0.002115526	0.068215262
-Ash2l.2130	Ash2l	23808	LIB	2130	1.241609259	1.460589922	1.022628597
-Asxl1.2020	Asxl1	228790	LIB	2020	0.059766771	0.009568839	0.109964703
-Asxl1.3548	Asxl1	228790	LIB	3548	0.10962211	0.118078719	0.101165501
-Asxl1.3785	Asxl1	228790	LIB	3785	0.418395785	0.701615799	0.135175771
-Asxl1.4792	Asxl1	228790	LIB	4792	0.292975143	0.202313712	0.383636573
-Asxl1.5221	Asxl1	228790	LIB	5221	NA	NA	NA
-Asxl1.6315	Asxl1	228790	LIB	6315	0.42809245	0.550629344	0.305555556
-Asxl2.11	Asxl2	75302	LIB	11	0.069299389	0.09512504	0.043473739
-Asxl2.4563	Asxl2	75302	LIB	4563	1.831446558	1.40504451	2.257848606
-Asxl2.6593	Asxl2	75302	LIB	6593	0.590189219	1.1171875	0.063190938
-Asxl2.7130	Asxl2	75302	LIB	7130	0.366813082	0.684577114	0.049049049
-Asxl2.7253	Asxl2	75302	LIB	7253	0.117667517	0	0.235335034
-Asxl3.6101	Asxl3	211961	LIB	6101	0.375913898	0.327116212	0.424711584
-Asxl3.6824	Asxl3	211961	LIB	6824	NA	NA	NA
-Asxl3.8947	Asxl3	211961	LIB	8947	0.296002749	0.122132318	0.469873181
-Asxl3.10021	Asxl3	211961	LIB	10021	0.026435101	0.00690583	0.045964372
-Asxl3.11070	Asxl3	211961	LIB	11070	0.049530555	0.063099738	0.035961372
-Asxl3.11073	Asxl3	211961	LIB	11073	0.027907605	0.003065917	0.052749293
-Atm.137	Atm	11920	LIB	137	6.47E-05	0.000129433	0
-Atm.4098	Atm	11920	LIB	4098	2.922281386	4.477807971	1.366754801
-Atm.4998	Atm	11920	LIB	4998	0	0	0
-Atm.5616	Atm	11920	LIB	5616	0.443498086	0.657270086	0.229726085
-Atm.7782	Atm	11920	LIB	7782	0.260352231	0.308840206	0.211864257
-Atm.9396	Atm	11920	LIB	9396	0.60032482	0.359381765	0.841267876
-Atr.1239	Atr	245000	LIB	1239	0.005067342	0	0.010134685
-Atr.3160	Atr	245000	LIB	3160	0	0	0
-Atr.4762	Atr	245000	LIB	4762	0.149038652	0.070833921	0.227243383
-Atr.6186	Atr	245000	LIB	6186	0.128457676	0.106936416	0.149978936
-Atr.7888	Atr	245000	LIB	7888	0.147861249	0.264325323	0.031397174
-Atrx.2490	Atrx	22589	LIB	2490	0.396582444	0.600036694	0.193128195
-Atrx.5490	Atrx	22589	LIB	5490	0.356515297	0.533129237	0.179901356
-Atrx.6144	Atrx	22589	LIB	6144	4.974521294	2.266989851	7.682052736
-Atrx.7173	Atrx	22589	LIB	7173	0.05387472	0.096820809	0.01092863
-Atrx.7377	Atrx	22589	LIB	7377	0.837321391	1.529071015	0.145571768
-Aurkb.520	Aurkb	20877	LIB	520	0.008388288	0.015122511	0.001654064
-Aurkb.631	Aurkb	20877	LIB	631	0.824053234	1.06458435	0.583522118
-Aurkb.917	Aurkb	20877	LIB	917	0.024491203	0.008743956	0.04023845
-Aurkb.928	Aurkb	20877	LIB	928	0.010416667	0	0.020833333
-Aurkb.1620	Aurkb	20877	LIB	1620	0	0	0
-Aurkb.1803	Aurkb	20877	LIB	1803	0.125188349	0.175752051	0.074624647
-Baz1a.2095	Baz1a	217578	LIB	2095	0.507940486	0.356679709	0.659201262
-Baz1a.2451	Baz1a	217578	LIB	2451	2.159026811	3.284734348	1.033319275
-Baz1a.4993	Baz1a	217578	LIB	4993	0.64349492	0.507178218	0.779811623
-Baz1a.5946	Baz1a	217578	LIB	5946	0.080389068	0.05529467	0.105483466
-Baz1b.801	Baz1b	22385	LIB	801	0.000639494	0.000888362	0.000390625
-Baz1b.3683	Baz1b	22385	LIB	3683	0.360095959	0.069445862	0.650746056
-Baz1b.5646	Baz1b	22385	LIB	5646	0.016297649	0.018375115	0.014220183
-Baz1b.6371	Baz1b	22385	LIB	6371	0.14306644	0	0.286132879
-Bmi1.698	Bmi1	12151	LIB	698	0.092709454	0.069620729	0.11579818
-Bmi1.895	Bmi1	12151	LIB	895	0.035594283	0.071188567	0
-Bmi1.1440	Bmi1	12151	LIB	1440	NA	NA	NA
-Bmi1.1746	Bmi1	12151	LIB	1746	0.118689343	0.122838849	0.114539838
-Bmi1.2404	Bmi1	12151	LIB	2404	0	0	0
-Bmi1.2561	Bmi1	12151	LIB	2561	0.454904159	0.631757214	0.278051103
-Bop1.778	Bop1	12181	LIB	778	0.672354814	0.445185419	0.899524209
-Bop1.2228	Bop1	12181	LIB	2228	0.142000285	0.127547666	0.156452904
-Bop1.2403	Bop1	12181	LIB	2403	0	0	0
-Bptf.1622	Bptf	207165	LIB	1622	0.077104921	0.08259276	0.071617083
-Bptf.3234	Bptf	207165	LIB	3234	0.057370498	0.065993919	0.048747077
-Bptf.7211	Bptf	207165	LIB	7211	0.024626408	0.021392709	0.027860107
-Bptf.8224	Bptf	207165	LIB	8224	0.410946348	0.179452295	0.6424404
-Braf.3750	Braf	109880	NC	3750	0.412381245	0.44332883	0.38143366
-Braf.3826	Braf	109880	NC	3826	0.129826198	0.1681838	0.091468596
-Braf.5053	Braf	109880	NC	5053	2.34833908	2.720656406	1.976021753
-Brd1.286	Brd1	223770	LIB	286	0.094299073	0.000374953	0.188223194
-Brd1.287	Brd1	223770	LIB	287	0.480557434	0.680387664	0.280727205
-Brd1.2096	Brd1	223770	LIB	2096	0.041243445	0.031141199	0.051345691
-Brd1.4229	Brd1	223770	LIB	4229	0.013231982	0.026463964	0
-Brd2.813	Brd2	14312	LIB	813	22.77961486	42.66701779	2.892211933
-Brd2.1714	Brd2	14312	LIB	1714	0.144143286	0.249835634	0.038450937
-Brd2.3011	Brd2	14312	LIB	3011	0.028355134	0.029962547	0.02674772
-Brd2.3396	Brd2	14312	LIB	3396	NA	NA	NA
-Brd3.187	Brd3	67382	LIB	187	3.11E-05	0	6.22E-05
-Brd3.298	Brd3	67382	LIB	298	0.056505575	0.058248337	0.054762814
-Brd3.411	Brd3	67382	LIB	411	0.756328621	1.503010235	0.009647007
-Brd3.4162	Brd3	67382	LIB	4162	0.633054482	0.738127854	0.52798111
-Brd4.523	Brd4	57261	LIB	523	0.010380898	0.004175644	0.016586151
-Brd4.552	Brd4	57261	LIB	552	0	0	0
-Brd4.632	Brd4	57261	LIB	632	0	0	0
-Brd4.1448	Brd4	57261	LIB	1448	0.135273343	0.118396988	0.152149699
-Brd4.2097	Brd4	57261	LIB	2097	0	0	0
-Carm1.892	Carm1	59035	LIB	892	0.079435576	0.000380084	0.158491069
-Carm1.1222	Carm1	59035	LIB	1222	0.075280112	0	0.150560224
-Carm1.1454	Carm1	59035	LIB	1454	0	0	0
-Carm1.1614	Carm1	59035	LIB	1614	0.243856333	0	0.487712665
-Carm1.1717	Carm1	59035	LIB	1717	0.001731885	0.002492331	0.00097144
-Cbx1.1004	Cbx1	12412	LIB	1004	0.057581903	0.083058046	0.03210576
-Cbx1.1053	Cbx1	12412	LIB	1053	1.091733912	0.589759684	1.593708139
-Cbx1.1099	Cbx1	12412	LIB	1099	0.57419689	0.919432666	0.228961114
-Cbx1.1103	Cbx1	12412	LIB	1103	0.458716872	0.142857143	0.774576601
-Cbx1.1210	Cbx1	12412	LIB	1210	0.245937138	0.37322759	0.118646686
-Cbx2.2033	Cbx2	12416	LIB	2033	0.134848542	0.001576873	0.268120212
-Cbx2.3537	Cbx2	12416	LIB	3537	0	0	0
-Cbx2.3545	Cbx2	12416	LIB	3545	0.710820484	1.275496689	0.146144279
-Cbx2.3620	Cbx2	12416	LIB	3620	0.134612189	0.008686441	0.260537937
-Cbx2.3706	Cbx2	12416	LIB	3706	1.147329284	1.49221144	0.802447127
-Cbx3.882	Cbx3	12417	LIB	882	0	0	0
-Cbx3.1206	Cbx3	12417	LIB	1206	0.118944773	0.131788129	0.106101417
-Cbx3.1339	Cbx3	12417	LIB	1339	0.142134201	0.070435009	0.213833393
-Cbx3.1719	Cbx3	12417	LIB	1719	0	0	0
-Cbx3.1735	Cbx3	12417	LIB	1735	0.115344034	0.011380552	0.219307515
-Cbx4.1794	Cbx4	12418	LIB	1794	1.364806716	0.371060327	2.358553106
-Cbx4.1844	Cbx4	12418	LIB	1844	0.700301215	1.223163842	0.177438588
-Cbx4.2573	Cbx4	12418	LIB	2573	0.817611719	0.890839629	0.744383809
-Cbx4.4403	Cbx4	12418	LIB	4403	0.215720626	0	0.431441252
-Cbx4.5120	Cbx4	12418	LIB	5120	0.497429027	0.398906637	0.595951417
-Cbx5.1309	Cbx5	12419	LIB	1309	0.986138423	0.975527017	0.996749828
-Cbx5.4366	Cbx5	12419	LIB	4366	0	0	0
-Cbx5.4409	Cbx5	12419	LIB	4409	0.18203172	0.15420805	0.20985539
-Cbx5.4508	Cbx5	12419	LIB	4508	0.693812292	0.764903255	0.622721329
-Cbx5.5707	Cbx5	12419	LIB	5707	0.232529345	0.127116437	0.337942253
-Cbx5.8586	Cbx5	12419	LIB	8586	0.176272377	0.350797267	0.001747488
-Cbx6.1535	Cbx6	494448	LIB	1535	1.317433547	0.026128266	2.608738828
-Cbx6.3332	Cbx6	494448	LIB	3332	0.628106622	1.114166972	0.142046271
-Cbx6.3473	Cbx6	494448	LIB	3473	1.362208923	0.193768257	2.530649588
-Cbx6.3969	Cbx6	494448	LIB	3969	0.591043966	0.80244028	0.379647652
-Cbx7.745	Cbx7	52609	LIB	745	0.218502726	0.203358299	0.233647153
-Cbx7.1633	Cbx7	52609	LIB	1633	0.040584859	0	0.081169719
-Cbx7.1634	Cbx7	52609	LIB	1634	0.075718892	0.000117758	0.151320026
-Cbx7.1639	Cbx7	52609	LIB	1639	0.100164464	0.124590164	0.075738763
-Cbx7.2006	Cbx7	52609	LIB	2006	0.080469517	0	0.160939034
-Cbx7.2504	Cbx7	52609	LIB	2504	0.038731085	0.004728435	0.072733736
-Cbx8.136	Cbx8	30951	LIB	136	0.110253195	0.038949338	0.181557052
-Cbx8.1120	Cbx8	30951	LIB	1120	0.226325463	0.218088273	0.234562653
-Cbx8.1342	Cbx8	30951	LIB	1342	1.082538396	1.289585162	0.87549163
-Chaf1a.166	Chaf1a	27221	LIB	166	0	0	0
-Chaf1a.1039	Chaf1a	27221	LIB	1039	0	0	0
-Chaf1a.2122	Chaf1a	27221	LIB	2122	0.397909545	0.698496344	0.097322746
-Chaf1b.367	Chaf1b	110749	LIB	367	0	0	0
-Chaf1b.566	Chaf1b	110749	LIB	566	0.303408945	0.482990787	0.123827104
-Chaf1b.692	Chaf1b	110749	LIB	692	0.287092522	0.574185043	0
-Chaf1b.901	Chaf1b	110749	LIB	901	0.20895781	0.141891892	0.276023728
-Chaf1b.1223	Chaf1b	110749	LIB	1223	0.040480317	0	0.080960634
-Chd1.746	Chd1	12648	LIB	746	0.109569072	0.112458184	0.10667996
-Chd1.1103	Chd1	12648	LIB	1103	0.03061677	0.03155467	0.029678869
-Chd1.2443	Chd1	12648	LIB	2443	0.119970268	0.110483782	0.129456754
-Chd1.2959	Chd1	12648	LIB	2959	0.204016851	0.209087277	0.198946425
-Chd1.4558	Chd1	12648	LIB	4558	0.579893278	1.122087605	0.037698952
-Chd1l.2305	Chd1l	68058	LIB	2305	0.171659277	0.161353286	0.181965268
-Chd1l.2598	Chd1l	68058	LIB	2598	0.064918568	0.001997004	0.127840131
-Chd1l.2804	Chd1l	68058	LIB	2804	0.320682295	0.225751283	0.415613308
-Chd2.926	Chd2	244059	LIB	926	0.138050187	0.180178767	0.095921607
-Chd2.3700	Chd2	244059	LIB	3700	0.397415785	0.434250439	0.360581131
-Chd2.3984	Chd2	244059	LIB	3984	0.134215951	0.080257186	0.188174716
-Chd2.8087	Chd2	244059	LIB	8087	0.189600975	0.263537572	0.115664379
-Chd2.8913	Chd2	244059	LIB	8913	0.073920542	0.106108526	0.041732558
-Chd3.482	Chd3	216848	LIB	482	0.08107178	0.014856739	0.147286822
-Chd3.3249	Chd3	216848	LIB	3249	0.071321859	0.011487304	0.131156413
-Chd3.4011	Chd3	216848	LIB	4011	0.289503582	0.42626498	0.152742183
-Chd3.6496	Chd3	216848	LIB	6496	0.044090494	0.030532487	0.057648502
-Chd3.7148	Chd3	216848	LIB	7148	2.340233512	1.930658742	2.749808282
-Chd3.7149	Chd3	216848	LIB	7149	0.156093321	0.116246872	0.19593977
-Chd4.2060	Chd4	107932	LIB	2060	0.000158747	0	0.000317494
-Chd4.3326	Chd4	107932	LIB	3326	NA	NA	NA
-Chd4.3423	Chd4	107932	LIB	3423	0.039003519	0.018129718	0.059877321
-Chd4.3772	Chd4	107932	LIB	3772	0.446854315	0.107456979	0.786251651
-Chd5.2301	Chd5	269610	LIB	2301	0.890171552	1.716215543	0.064127562
-Chd5.2900	Chd5	269610	LIB	2900	2.179569236	1.422986617	2.936151855
-Chd5.5471	Chd5	269610	LIB	5471	0.031951327	0.008029979	0.055872675
-Chd5.6392	Chd5	269610	LIB	6392	1.431979693	1.532967033	1.330992354
-Chd6.311	Chd6	71389	LIB	311	0.034464804	0.005788154	0.063141455
-Chd6.4698	Chd6	71389	LIB	4698	0.079293047	0.058312236	0.100273857
-Chd6.4988	Chd6	71389	LIB	4988	0.706143751	0.96534451	0.446942993
-Chd6.9610	Chd6	71389	LIB	9610	0.621464656	0.915195867	0.327733445
-Chd7.1269	Chd7	320790	LIB	1269	4.781464099	6.785229842	2.777698356
-Chd7.1502	Chd7	320790	LIB	1502	0.778617907	1.132855191	0.424380624
-Chd7.5857	Chd7	320790	LIB	5857	1.176684021	1.753802163	0.599565878
-Chd7.6498	Chd7	320790	LIB	6498	0.554422725	0.923791103	0.185054348
-Chd7.7229	Chd7	320790	LIB	7229	1.1593543	0.786077021	1.532631579
-Chd8.434	Chd8	67772	LIB	434	0.240881821	0.481763642	0
-Chd8.3265	Chd8	67772	LIB	3265	2.777624937	3.217093529	2.338156344
-Chd8.4169	Chd8	67772	LIB	4169	2.352884012	2.797262325	1.908505699
-Chd8.5352	Chd8	67772	LIB	5352	0.046980193	0	0.093960386
-Chd8.6946	Chd8	67772	LIB	6946	0.082319013	0.141659648	0.022978377
-Chd9.1402	Chd9	109151	LIB	1402	2.015703082	1.209699299	2.821706865
-Chd9.3919	Chd9	109151	LIB	3919	0.232392142	0.178955954	0.285828331
-Chd9.9352	Chd9	109151	LIB	9352	0.063600987	0.001541511	0.125660464
-Chd9.10928	Chd9	109151	LIB	10928	0.281642373	0.071780078	0.491504669
-Clock.693	Clock	12753	LIB	693	4.165656967	6.332554466	1.998759467
-Clock.1387	Clock	12753	LIB	1387	0.154177662	0.004555809	0.303799515
-Clock.4461	Clock	12753	LIB	4461	2.081932577	1.782110872	2.381754283
-Clock.4611	Clock	12753	LIB	4611	0.186897319	0.248041429	0.125753209
-Clock.5863	Clock	12753	LIB	5863	0	0	0
-Crebbp.704	Crebbp	12914	LIB	704	11.9485048	19.00330745	4.893702157
-Crebbp.2064	Crebbp	12914	LIB	2064	1.188115541	1.435698153	0.940532929
-Crebbp.2118	Crebbp	12914	LIB	2118	0.053391885	0.024676711	0.082107059
-Crebbp.3582	Crebbp	12914	LIB	3582	3.655607969	4.58780241	2.723413529
-Crebbp.4463	Crebbp	12914	LIB	4463	16.37310333	22.75705636	9.989150297
-Ctsl.940	Ctsl	13039	LIB	940	0.566559532	0.631030822	0.502088243
-Ctsl.1445	Ctsl	13039	LIB	1445	1.390909314	2.649395911	0.132422717
-Ctsl.1941	Ctsl	13039	LIB	1941	0.066051589	0.007621849	0.124481328
-Ctsl.1942	Ctsl	13039	LIB	1942	0.096645722	0.171270718	0.022020725
-Ctsl.1947	Ctsl	13039	LIB	1947	0.615592343	0.666345784	0.564838903
-Cxxc1.68	Cxxc1	74322	LIB	68	0.47853168	0.342590096	0.614473263
-Cxxc1.359	Cxxc1	74322	LIB	359	0.024227576	0	0.048455152
-Cxxc1.1889	Cxxc1	74322	LIB	1889	0.063713733	0.00804721	0.119380256
-Cxxc1.2034	Cxxc1	74322	LIB	2034	0.345104593	0.226497717	0.463711468
-Cxxc1.2133	Cxxc1	74322	LIB	2133	0.198889771	0.198522247	0.199257294
-Dmap1.439	Dmap1	66233	LIB	439	0.703875338	0.77262223	0.635128445
-Dmap1.518	Dmap1	66233	LIB	518	NA	NA	NA
-Dmap1.1354	Dmap1	66233	LIB	1354	0.14763293	0.098111837	0.197154022
-Dmap1.1355	Dmap1	66233	LIB	1355	0.42757955	0.089182969	0.765976131
-Dmap1.1487	Dmap1	66233	LIB	1487	1.398029255	2.142666181	0.65339233
-Dnmt1.437	Dnmt1	13433	LIB	437	0.216593143	0.00036049	0.432825795
-Dnmt1.828	Dnmt1	13433	LIB	828	0.031108522	0	0.062217045
-Dnmt1.1137	Dnmt1	13433	LIB	1137	0	0	0
-Dnmt1.4462	Dnmt1	13433	LIB	4462	0.107595678	0.084457173	0.130734182
-Dnmt1.4848	Dnmt1	13433	LIB	4848	2.73965767	4.554970263	0.924345077
-Dnmt3a.16	Dnmt3a	13435	LIB	16	1.725217186	1.842114421	1.608319951
-Dnmt3a.1669	Dnmt3a	13435	LIB	1669	0.151960261	0.274109644	0.029810877
-Dnmt3a.2338	Dnmt3a	13435	LIB	2338	0.464228303	0.546660024	0.381796582
-Dnmt3a.4173	Dnmt3a	13435	LIB	4173	2.839755061	1.630561738	4.048948383
-Dnmt3b.275	Dnmt3b	13436	LIB	275	0.111149425	0	0.222298851
-Dnmt3b.579	Dnmt3b	13436	LIB	579	0.190916889	0.103235294	0.278598485
-Dnmt3b.958	Dnmt3b	13436	LIB	958	0.051940249	0.10105972	0.002820777
-Dnmt3b.2218	Dnmt3b	13436	LIB	2218	0	0	0
-Dnmt3l.306	Dnmt3l	54427	LIB	306	0.009228421	0	0.018456842
-Dnmt3l.760	Dnmt3l	54427	LIB	760	0.639860874	0.834630621	0.445091128
-Dnmt3l.1049	Dnmt3l	54427	LIB	1049	0.275136367	0.291147084	0.25912565
-Dnmt3l.1333	Dnmt3l	54427	LIB	1333	0.729534649	0.550112191	0.908957107
-Dnmt3l.1350	Dnmt3l	54427	LIB	1350	0.869186931	1.148524754	0.589849108
-Dot1l.602	Dot1l	208266	LIB	602	0.052820647	0.104150504	0.001490789
-Dot1l.941	Dot1l	208266	LIB	941	NA	NA	NA
-Dot1l.3626	Dot1l	208266	LIB	3626	0	0	0
-Dub2a.769	Dub2a	384701	LIB	769	1.538125565	2.261141129	0.815110001
-Dub2a.1334	Dub2a	384701	LIB	1334	0.311123833	0.274834437	0.347413229
-Dub2a.1391	Dub2a	384701	LIB	1391	0	0	0
-Dub2a.1397	Dub2a	384701	LIB	1397	0.92660009	0.741578683	1.111621497
-Dub2a.1444	Dub2a	384701	LIB	1444	0.129914681	0.128666667	0.131162695
-Dub2a.1445	Dub2a	384701	LIB	1445	0.313809229	0.308336591	0.319281867
-Edf1.486	Edf1	59022	LIB	486	0.584392451	0.593347689	0.575437213
-Edf1.628	Edf1	59022	LIB	628	0.631092498	1.048248699	0.213936297
-Edf1.631	Edf1	59022	LIB	631	0.211734062	0.293841091	0.129627033
-Edf1.652	Edf1	59022	LIB	652	0.133434746	0.188121528	0.078747964
-Eed.710	Eed	13626	LIB	710	0	0	0
-Eed.949	Eed	13626	LIB	949	0.716286619	0.796963648	0.63560959
-Eed.1083	Eed	13626	LIB	1083	0.029501785	0.041323731	0.017679838
-Eed.1397	Eed	13626	LIB	1397	0.246827441	0.148140193	0.345514689
-Eed.1820	Eed	13626	LIB	1820	1.45400601	2.707134121	0.200877898
-EG330129.869	EG330129	330129	LIB	869	0.174185305	0.022923713	0.325446898
-EG330129.2118	EG330129	330129	LIB	2118	0.182159211	0.070402494	0.293915929
-EG330129.2262	EG330129	330129	LIB	2262	1.326585139	1.239206534	1.413963743
-EG330129.2329	EG330129	330129	LIB	2329	0.216031756	0.316051389	0.116012124
-EG546387.1344	EG546387	546387	LIB	1344	1.884762179	2.164840532	1.604683826
-EG546387.2159	EG546387	546387	LIB	2159	0.330597641	0.293600259	0.367595023
-EG546387.2272	EG546387	546387	LIB	2272	0.382783292	0.430418838	0.335147745
-Ehmt1.66	Ehmt1	77683	LIB	66	0.211522228	0.16763608	0.255408376
-Ehmt1.386	Ehmt1	77683	LIB	386	0.163750658	0.113922928	0.213578389
-Ehmt1.859	Ehmt1	77683	LIB	859	0	0	0
-Ehmt1.920	Ehmt1	77683	LIB	920	2.134228281	3.754773552	0.51368301
-Ehmt1.3003	Ehmt1	77683	LIB	3003	0.000117585	0.00023517	0
-Ehmt2.724	Ehmt2	110147	LIB	724	0.448962106	0.525151398	0.372772814
-Ehmt2.1880	Ehmt2	110147	LIB	1880	0.120154259	0.044799208	0.19550931
-Ehmt2.2014	Ehmt2	110147	LIB	2014	0.391040713	0.240246192	0.541835234
-Ehmt2.3146	Ehmt2	110147	LIB	3146	0.23467894	0.240075706	0.229282175
-Ehmt2.3202	Ehmt2	110147	LIB	3202	0.038002797	0.076005593	0
-Elp3.117	Elp3	74195	LIB	117	0.373058626	0.121392815	0.624724436
-Elp3.215	Elp3	74195	LIB	215	0.047358662	0.093162219	0.001555105
-Elp3.219	Elp3	74195	LIB	219	0.054251126	0.007308659	0.101193592
-Elp3.592	Elp3	74195	LIB	592	0.016186053	0.000130702	0.032241405
-Ep300.754	Ep300	328572	LIB	754	0.621685394	0.695170261	0.548200527
-Ep300.3850	Ep300	328572	LIB	3850	0	0	0
-Ep300.5490	Ep300	328572	LIB	5490	0.109121897	0.125441696	0.092802099
-Ep300.7826	Ep300	328572	LIB	7826	0.066538139	0.12088261	0.012193669
-Ep300.8647	Ep300	328572	LIB	8647	0.268474952	0.379490888	0.157459016
-Evi1.649	Evi1	14013	LIB	649	0.041338867	0.042903321	0.039774414
-Evi1.652	Evi1	14013	LIB	652	0.702939444	0.290198461	1.115680427
-Evi1.1371	Evi1	14013	LIB	1371	0.655772594	0.660998268	0.65054692
-Evi1.1978	Evi1	14013	LIB	1978	NA	NA	NA
-Evi1.2720	Evi1	14013	LIB	2720	0.5472099	0.513677435	0.580742364
-Ezh1.68	Ezh1	14055	LIB	68	0.645375689	0.276368717	1.01438266
-Ezh1.73	Ezh1	14055	LIB	73	0.545034582	0.000464684	1.08960448
-Ezh1.4104	Ezh1	14055	LIB	4104	0.161312023	0.013273543	0.309350504
-Ezh1.4105	Ezh1	14055	LIB	4105	0.171634666	0	0.343269333
-Ezh2.556	Ezh2	14056	LIB	556	0.466252547	0.612704524	0.31980057
-Ezh2.1370	Ezh2	14056	LIB	1370	0.123390861	7.64E-05	0.246705356
-Ezh2.1678	Ezh2	14056	LIB	1678	0.929056053	0.842508957	1.015603148
-Ezh2.2124	Ezh2	14056	LIB	2124	0.31242234	0.550174697	0.074669984
-Ezh2.2253	Ezh2	14056	LIB	2253	0.01894361	0.035966931	0.001920288
-Fbxl10.356	Fbxl10	30841	LIB	356	0.784501754	0.743513957	0.825489551
-Fbxl10.443	Fbxl10	30841	LIB	443	0	0	0
-Fbxl10.3131	Fbxl10	30841	LIB	3131	0.334422325	0.322283458	0.346561192
-Fbxl10.3145	Fbxl10	30841	LIB	3145	7.832968832	5.033134824	10.63280284
-Fbxl11.663	Fbxl11	225876	LIB	663	0.055910099	0.056709087	0.055111111
-Fbxl11.1840	Fbxl11	225876	LIB	1840	0.665785489	0.545696539	0.785874439
-Fbxl11.7144	Fbxl11	225876	LIB	7144	0.429356479	0.627018076	0.231694881
-Fbxl11.7145	Fbxl11	225876	LIB	7145	0.022754725	0.006901311	0.03860814
-Fbxl19.1945	Fbxl19	233902	LIB	1945	0.000400481	0.000800961	0
-Fbxl19.2841	Fbxl19	233902	LIB	2841	0	0	0
-Fbxl19.3203	Fbxl19	233902	LIB	3203	0.009336737	0	0.018673474
-Fkbp1a.646	Fkbp1a	14225	LIB	646	0.013864068	0.000782983	0.026945153
-Fkbp1a.827	Fkbp1a	14225	LIB	827	9.3066783	17.8021978	0.811158798
-Fkbp1a.851	Fkbp1a	14225	LIB	851	0.000933707	0.001867414	0
-Fkbp1a.854	Fkbp1a	14225	LIB	854	0.231878127	0.293098599	0.170657654
-Fkbp2.195	Fkbp2	14227	LIB	195	0.069369424	0.006895419	0.131843428
-Fkbp2.213	Fkbp2	14227	LIB	213	0	0	0
-Fkbp2.532	Fkbp2	14227	LIB	532	NA	NA	NA
-Fkbp2.581	Fkbp2	14227	LIB	581	0.082910366	0.073922933	0.091897799
-Fkbp5.595	Fkbp5	14229	LIB	595	0.338439879	0.280911589	0.39596817
-Fkbp5.628	Fkbp5	14229	LIB	628	0.089209903	0.17644742	0.001972387
-Fkbp5.1219	Fkbp5	14229	LIB	1219	0.000883913	0	0.001767826
-Fkbp5.2613	Fkbp5	14229	LIB	2613	NA	NA	NA
-Fkbp5.2813	Fkbp5	14229	LIB	2813	1.309441349	0	2.618882698
-Fkbp5.3272	Fkbp5	14229	LIB	3272	0.077016559	0.100727476	0.053305642
-Gtf3c4.2358	Gtf3c4	269252	LIB	2358	0.307657393	0.515803397	0.099511389
-Gtf3c4.2444	Gtf3c4	269252	LIB	2444	0.211577111	0.019757689	0.403396534
-Gtf3c4.2605	Gtf3c4	269252	LIB	2605	2.594960462	3.356335785	1.833585138
-Gtf3c4.3160	Gtf3c4	269252	LIB	3160	0.218403794	0.156206756	0.280600831
-Gtf3c4.3163	Gtf3c4	269252	LIB	3163	0.706197905	0.944937527	0.467458283
-H2afz.508	H2afz	51788	LIB	508	0.112249335	0.190899582	0.033599089
-H2afz.692	H2afz	51788	LIB	692	0.119788095	0.10965435	0.12992184
-H2afz.823	H2afz	51788	LIB	823	0	0	0
-H2afz.909	H2afz	51788	LIB	909	2.570129526	3.94702491	1.193234141
-H2afz.937	H2afz	51788	LIB	937	0.262185545	0.243682034	0.280689056
-Hat1.290	Hat1	107435	LIB	290	0.242612885	0.28585051	0.19937526
-Hat1.638	Hat1	107435	LIB	638	1.347345343	1.429206206	1.265484481
-Hat1.866	Hat1	107435	LIB	866	0.629381934	0.736795839	0.521968029
-Hat1.1528	Hat1	107435	LIB	1528	0.415532045	0.51072454	0.320339551
-Hcfc1.812	Hcfc1	15161	LIB	812	0.162841158	0.15639547	0.169286845
-Hcfc1.4648	Hcfc1	15161	LIB	4648	0.063853471	0	0.127706942
-Hcfc1.7430	Hcfc1	15161	LIB	7430	0.024043164	0.037148827	0.0109375
-Hcfc1.7506	Hcfc1	15161	LIB	7506	0.133648563	0.20077669	0.066520435
-Hcfc1.8014	Hcfc1	15161	LIB	8014	0.001865461	0.003730921	0
-Hdac1.245	Hdac1	433759	LIB	245	0.23785439	0.369592346	0.106116433
-Hdac1.1053	Hdac1	433759	LIB	1053	0.441444289	0.704354469	0.17853411
-Hdac1.1065	Hdac1	433759	LIB	1065	0.003350221	0.006700441	0
-Hdac1.1830	Hdac1	433759	LIB	1830	1.267186229	0.331748957	2.2026235
-Hdac10.1645	Hdac10	170787	LIB	1645	NA	NA	NA
-Hdac10.2041	Hdac10	170787	LIB	2041	0.034962353	0.003184375	0.066740331
-Hdac10.2307	Hdac10	170787	LIB	2307	0.244272107	0.406371338	0.082172877
-Hdac11.2025	Hdac11	232232	LIB	2025	0.034038791	0.067849687	0.000227894
-Hdac11.2058	Hdac11	232232	LIB	2058	0.616567512	0.530961372	0.702173652
-Hdac11.2182	Hdac11	232232	LIB	2182	0	0	0
-Hdac11.2460	Hdac11	232232	LIB	2460	0.179395578	0.071746032	0.287045124
-Hdac11.2461	Hdac11	232232	LIB	2461	0.106169791	0.145963878	0.066375705
-Hdac2.439	Hdac2	15182	LIB	439	0.120428617	0.098365041	0.142492194
-Hdac2.440	Hdac2	15182	LIB	440	0	0	0
-Hdac2.1184	Hdac2	15182	LIB	1184	1.736519405	1.729724166	1.743314643
-Hdac2.1611	Hdac2	15182	LIB	1611	0.555755616	0.901804888	0.209706344
-Hdac2.1919	Hdac2	15182	LIB	1919	0.22681503	0.273884154	0.179745907
-Hdac3.161	Hdac3	15183	LIB	161	0.027585567	0.052225083	0.00294605
-Hdac3.854	Hdac3	15183	LIB	854	0.19703596	0.313846421	0.080225499
-Hdac3.987	Hdac3	15183	LIB	987	9.200089463	15.16698706	3.23319187
-Hdac3.1037	Hdac3	15183	LIB	1037	0.194075242	0.388150484	0
-Hdac3.1491	Hdac3	15183	LIB	1491	0.078428253	0	0.156856507
-Hdac4.331	Hdac4	208727	LIB	331	0.249392869	0.421878803	0.076906935
-Hdac4.431	Hdac4	208727	LIB	431	12.91595763	23.42054693	2.41136833
-Hdac4.1903	Hdac4	208727	LIB	1903	0.656722465	0.484156227	0.829288703
-Hdac4.3273	Hdac4	208727	LIB	3273	0.086063916	0.063287745	0.108840087
-Hdac5.1115	Hdac5	15184	LIB	1115	0.146091516	0.292183031	0
-Hdac5.1936	Hdac5	15184	LIB	1936	0.311596614	0.41754442	0.205648809
-Hdac5.2060	Hdac5	15184	LIB	2060	0.050833282	0.001168224	0.100498339
-Hdac5.2412	Hdac5	15184	LIB	2412	0.153710614	7.29E-05	0.307348299
-Hdac5.2886	Hdac5	15184	LIB	2886	0.023975817	0.024090462	0.023861171
-Hdac6.530	Hdac6	15185	LIB	530	NA	NA	NA
-Hdac6.2249	Hdac6	15185	LIB	2249	0.395188053	0.790376106	0
-Hdac6.3838	Hdac6	15185	LIB	3838	0.463447784	0.373127484	0.553768085
-Hdac6.4026	Hdac6	15185	LIB	4026	0.673906334	0.58012685	0.767685818
-Hdac7.560	Hdac7	56233	LIB	560	0.05	0.1	0
-Hdac7.836	Hdac7	56233	LIB	836	1.003143594	0.60732691	1.398960277
-Hdac7.1293	Hdac7	56233	LIB	1293	0.232796973	0.260955434	0.204638512
-Hdac7.2255	Hdac7	56233	LIB	2255	0.180458299	0.321948649	0.038967948
-Hdac7.3429	Hdac7	56233	LIB	3429	0.108629839	0.07593243	0.141327247
-Hdac8.296	Hdac8	70315	LIB	296	0	0	0
-Hdac8.397	Hdac8	70315	LIB	397	0.346191954	0.376371183	0.316012725
-Hdac8.900	Hdac8	70315	LIB	900	0.06905	0.066867307	0.071232693
-Hdac8.1692	Hdac8	70315	LIB	1692	0.716122809	0.945390961	0.486854657
-Hdac9.1236	Hdac9	79221	LIB	1236	0.061659427	0.057717972	0.065600882
-Hdac9.1449	Hdac9	79221	LIB	1449	0.043527072	0.053540314	0.03351383
-Hdac9.2031	Hdac9	79221	LIB	2031	0.20955986	0.268333519	0.1507862
-Hdac9.2070	Hdac9	79221	LIB	2070	0.237782658	0.104923474	0.370641842
-Hdac9.4083	Hdac9	79221	LIB	4083	0.385634864	0.501316194	0.269953535
-Hells.977	Hells	15201	LIB	977	0.412970986	0.000769823	0.82517215
-Hells.1094	Hells	15201	LIB	1094	NA	NA	NA
-Hells.1145	Hells	15201	LIB	1145	0.069970575	0.086036762	0.053904388
-Hells.1703	Hells	15201	LIB	1703	1.268695155	1.091805094	1.445585216
-Hells.2323	Hells	15201	LIB	2323	0.098153695	0.146551233	0.049756158
-Hira.223	Hira	15260	LIB	223	0.038783499	0.047608174	0.029958824
-Hira.2318	Hira	15260	LIB	2318	0	0	0
-Hira.2835	Hira	15260	LIB	2835	1.729519941	2.66571554	0.793324343
-Hira.4298	Hira	15260	LIB	4298	0.054981253	0.011631924	0.098330582
-Hltf.252	Hltf	20585	LIB	252	0.405465225	0.538874518	0.272055932
-Hltf.455	Hltf	20585	LIB	455	0.441636316	0.589916076	0.293356556
-Hltf.497	Hltf	20585	LIB	497	3.701953893	1.507171929	5.896735857
-Hltf.1198	Hltf	20585	LIB	1198	0.200363394	0.039606523	0.361120264
-Ing2.649	Ing2	69260	LIB	649	0.026442538	0.001332149	0.051552926
-Ing2.1400	Ing2	69260	LIB	1400	0.441872864	0.485687809	0.398057919
-Ing2.1788	Ing2	69260	LIB	1788	0.00514048	0.009192066	0.001088893
-Ing2.1824	Ing2	69260	LIB	1824	0.230878224	0.327220173	0.134536275
-Ing2.2176	Ing2	69260	LIB	2176	0.110401249	0.03625	0.184552498
-Ino80.458	Ino80	68142	LIB	458	1.017141522	0.572352773	1.461930271
-Ino80.1194	Ino80	68142	LIB	1194	0.864776346	0.582272727	1.147279965
-Ino80.2062	Ino80	68142	LIB	2062	3.479477858	2.83947293	4.119482786
-Ino80.4069	Ino80	68142	LIB	4069	4.925644667	4.280960907	5.570328426
-Jarid1a.2826	Jarid1a	214899	LIB	2826	0.248654315	0.35031185	0.14699678
-Jarid1a.6729	Jarid1a	214899	LIB	6729	1.363948366	0.535007243	2.192889488
-Jarid1a.10299	Jarid1a	214899	LIB	10299	0.263122123	0.241511541	0.284732705
-Jarid1a.10802	Jarid1a	214899	LIB	10802	0.106583794	0	0.213167587
-Jarid1a.11640	Jarid1a	214899	LIB	11640	0.311471985	0.488261591	0.134682379
-Jarid1b.382	Jarid1b	75605	LIB	382	0.18904701	0.27594244	0.10215158
-Jarid1b.1671	Jarid1b	75605	LIB	1671	NA	NA	NA
-Jarid1b.2176	Jarid1b	75605	LIB	2176	NA	NA	NA
-Jarid1b.4339	Jarid1b	75605	LIB	4339	0.192060819	0.068007096	0.316114542
-Jarid1b.4527	Jarid1b	75605	LIB	4527	0.071297514	0.00530504	0.137289989
-Jarid1c.1882	Jarid1c	20591	LIB	1882	0.140338666	0.006669282	0.274008051
-Jarid1c.1886	Jarid1c	20591	LIB	1886	0.69700856	0.5224761	0.871541021
-Jarid1c.2010	Jarid1c	20591	LIB	2010	0.918964146	1.082710075	0.755218216
-Jarid1c.5632	Jarid1c	20591	LIB	5632	1.124564108	1.80619245	0.442935765
-Jarid1d.2138	Jarid1d	20592	LIB	2138	0.012383228	0.024766457	0
-Jarid1d.2800	Jarid1d	20592	LIB	2800	0.587157188	0.988469407	0.185844969
-Jarid1d.3002	Jarid1d	20592	LIB	3002	0.080944165	0.06776283	0.094125501
-Jarid1d.4830	Jarid1d	20592	LIB	4830	0.383022948	0.353332365	0.412713531
-Jarid2.1699	Jarid2	16468	LIB	1699	0.157375244	0.267980636	0.046769852
-Jarid2.2191	Jarid2	16468	LIB	2191	2.421585425	4.080815103	0.762355747
-Jarid2.3219	Jarid2	16468	LIB	3219	0	0	0
-Jhdm1d.2087	Jhdm1d	338523	LIB	2087	0.258961381	0.414341695	0.103581067
-Jhdm1d.2209	Jhdm1d	338523	LIB	2209	0.617600335	0.548194175	0.687006494
-Jhdm1d.3273	Jhdm1d	338523	LIB	3273	0.225125817	0.192359317	0.257892316
-Jhdm1d.6787	Jhdm1d	338523	LIB	6787	0.134739676	0.083890257	0.185589094
-Jhdm1d.8524	Jhdm1d	338523	LIB	8524	0.28018788	0.280165234	0.280210526
-Jmjd1a.371	Jmjd1a	104263	LIB	371	0	0	0
-Jmjd1a.753	Jmjd1a	104263	LIB	753	0.02953012	0.007313698	0.051746541
-Jmjd1a.1070	Jmjd1a	104263	LIB	1070	0.084311633	0	0.168623266
-Jmjd1a.3518	Jmjd1a	104263	LIB	3518	0.495965201	0.000211595	0.991718808
-Jmjd1b.1014	Jmjd1b	277250	LIB	1014	0.872781647	0.739329604	1.006233691
-Jmjd1b.3708	Jmjd1b	277250	LIB	3708	0.000261472	0	0.000522944
-Jmjd1b.5309	Jmjd1b	277250	LIB	5309	0.565075338	0.33739665	0.792754026
-Jmjd1b.6406	Jmjd1b	277250	LIB	6406	1.329007355	0.941659685	1.716355024
-Jmjd1b.6504	Jmjd1b	277250	LIB	6504	0.554591185	0.173112518	0.936069851
-Jmjd1c.649	Jmjd1c	108829	LIB	649	0.300678085	0.162322666	0.439033504
-Jmjd1c.3196	Jmjd1c	108829	LIB	3196	0.000842912	0.001685824	0
-Jmjd1c.4221	Jmjd1c	108829	LIB	4221	0.103679501	0.106351828	0.101007173
-Jmjd1c.6050	Jmjd1c	108829	LIB	6050	0.726982674	0.553239773	0.900725575
-Jmjd1c.6346	Jmjd1c	108829	LIB	6346	0.230741091	0.167158309	0.294323873
-Jmjd2a.424	Jmjd2a	230674	LIB	424	0.207264965	0.120808561	0.293721369
-Jmjd2a.663	Jmjd2a	230674	LIB	663	0.113322058	0.075793595	0.15085052
-Jmjd2a.1474	Jmjd2a	230674	LIB	1474	0.08913639	0.002784366	0.175488414
-Jmjd2a.1498	Jmjd2a	230674	LIB	1498	0.043079662	0.069152399	0.017006925
-Jmjd2a.3033	Jmjd2a	230674	LIB	3033	0.000831282	0.001034029	0.000628536
-Jmjd2b.1151	Jmjd2b	193796	LIB	1151	0.933461944	1.175144551	0.691779336
-Jmjd2b.2905	Jmjd2b	193796	LIB	2905	1.786480339	2.379093311	1.193867366
-Jmjd2b.4018	Jmjd2b	193796	LIB	4018	1.348195558	1.050841453	1.645549663
-Jmjd2b.4170	Jmjd2b	193796	LIB	4170	0.895988133	0.355499082	1.436477183
-Jmjd2c.738	Jmjd2c	76804	LIB	738	0.187741857	0.120085677	0.255398037
-Jmjd2c.1217	Jmjd2c	76804	LIB	1217	1.318076072	0.96347543	1.672676713
-Jmjd2c.3112	Jmjd2c	76804	LIB	3112	0.412965767	0.468026197	0.357905337
-Jmjd2c.3541	Jmjd2c	76804	LIB	3541	0.480747339	0.556819876	0.404674802
-Jmjd2d.301	Jmjd2d	244694	LIB	301	0.129064364	0.000328623	0.257800106
-Jmjd2d.450	Jmjd2d	244694	LIB	450	1.353922306	0.000965251	2.706879362
-Jmjd2d.1143	Jmjd2d	244694	LIB	1143	0.490140075	0.956008305	0.024271845
-Jmjd2d.2310	Jmjd2d	244694	LIB	2310	0.164979808	0.256726348	0.073233268
-Jmjd2d.2358	Jmjd2d	244694	LIB	2358	0.059442746	0.07510305	0.043782442
-Jmjd4.1722	Jmjd4	194952	LIB	1722	0.741528975	0.765657556	0.717400394
-Jmjd4.1796	Jmjd4	194952	LIB	1796	0.200102959	0.163622609	0.23658331
-Jmjd4.2677	Jmjd4	194952	LIB	2677	0.676849819	0.820704579	0.532995059
-Jmjd4.2749	Jmjd4	194952	LIB	2749	0.15829753	0.038494735	0.278100325
-Jmjd4.3327	Jmjd4	194952	LIB	3327	0.553203122	0.185103308	0.921302937
-Jmjd5.18	Jmjd5	77035	LIB	18	2.587739528	3.744000541	1.431478516
-Jmjd5.1123	Jmjd5	77035	LIB	1123	0.148414474	0.037384899	0.259444048
-Jmjd5.1291	Jmjd5	77035	LIB	1291	0.401904979	0.407221471	0.396588486
-Jmjd5.1564	Jmjd5	77035	LIB	1564	0.186949478	0.022460197	0.351438759
-Jmjd5.2041	Jmjd5	77035	LIB	2041	0.008618272	0.016029948	0.001206596
-Jmjd6.254	Jmjd6	107817	LIB	254	0.12362466	0.184941628	0.062307692
-Jmjd6.530	Jmjd6	107817	LIB	530	0.147628799	0.026531729	0.268725869
-Jmjd6.956	Jmjd6	107817	LIB	956	0.132745115	0.260845889	0.004644341
-Jmjd6.1633	Jmjd6	107817	LIB	1633	0.240665022	0.253816286	0.227513757
-Kat2a.542	Kat2a	14534	LIB	542	0.618565777	0.940924658	0.296206897
-Kat2a.1771	Kat2a	14534	LIB	1771	0.120971403	0	0.241942805
-Kat2a.2053	Kat2a	14534	LIB	2053	0.538437996	0.10757034	0.969305652
-Kat2a.2201	Kat2a	14534	LIB	2201	0.142403868	0.257946389	0.026861346
-Kat2b.1306	Kat2b	18519	LIB	1306	0.040373807	0.071984908	0.008762706
-Kat2b.2624	Kat2b	18519	LIB	2624	0.079970208	0.073811384	0.086129032
-Kat2b.3228	Kat2b	18519	LIB	3228	0.069588311	0.063063063	0.076113558
-Kat2b.3494	Kat2b	18519	LIB	3494	0.369201025	0.457417016	0.280985033
-Kat2b.3766	Kat2b	18519	LIB	3766	0.111142996	0.145979608	0.076306385
-Kat5.679	Kat5	81601	LIB	679	0.117228687	0.230010953	0.004446421
-Kat5.1193	Kat5	81601	LIB	1193	2.307918926	2.68596882	1.929869033
-Kat5.1242	Kat5	81601	LIB	1242	NA	NA	NA
-Kat5.1387	Kat5	81601	LIB	1387	3.821357363	3.433995327	4.208719399
-L3mbtl.263	L3mbtl	241764	LIB	263	0.199214313	0.000694806	0.39773382
-L3mbtl.373	L3mbtl	241764	LIB	373	0.290562147	0.414519609	0.166604686
-L3mbtl.725	L3mbtl	241764	LIB	725	0.389300951	0.33340748	0.445194422
-L3mbtl.1906	L3mbtl	241764	LIB	1906	0.01201515	0.024030299	0
-L3mbtl.2689	L3mbtl	241764	LIB	2689	0.068187318	0.136374637	0
-LOC100040412.49	LOC100040412	100040412	LIB	49	0.235139043	0.216814556	0.253463531
-LOC100040412.495	LOC100040412	100040412	LIB	495	NA	NA	NA
-LOC100040412.655	LOC100040412	100040412	LIB	655	0.385744528	0.194355059	0.577133998
-LOC100040412.1128	LOC100040412	100040412	LIB	1128	0.321175793	0.350280264	0.292071322
-LOC100044324.736	LOC100044324	100044324	LIB	736	0.541107405	0.527171897	0.555042912
-LOC100044324.927	LOC100044324	100044324	LIB	927	0.174749605	0.349499209	0
-LOC100044324.1075	LOC100044324	100044324	LIB	1075	4.38507001	5.72404439	3.046095631
-LOC100044324.1240	LOC100044324	100044324	LIB	1240	0.248179872	0	0.496359743
-LOC100044324.1314	LOC100044324	100044324	LIB	1314	0.215962555	0.146174702	0.285750408
-LOC100048887.186	LOC100048887	100048887	LIB	186	4.761125427	3.672516129	5.849734725
-LOC100048887.194	LOC100048887	100048887	LIB	194	0	0	0
-LOC100048887.732	LOC100048887	100048887	LIB	732	0.074897582	0.110762101	0.039033064
-LOC100048887.787	LOC100048887	100048887	LIB	787	0	0	0
-LOC100048887.803	LOC100048887	100048887	LIB	803	0.116716316	0.079717133	0.153715499
-LOC664892.1494	LOC664892	664892	LIB	1494	0.568467589	0.647703684	0.489231493
-LOC664892.1500	LOC664892	664892	LIB	1500	0.82744825	1.141203528	0.513692971
-LOC664892.1697	LOC664892	664892	LIB	1697	0.363859691	0.15822698	0.569492403
-LOC664892.1892	LOC664892	664892	LIB	1892	0.09125886	0.026162019	0.156355701
-LOC664892.2169	LOC664892	664892	LIB	2169	0.011900813	0.022360704	0.001440922
-Mbd1.746	Mbd1	17190	LIB	746	0.194643294	0.000376081	0.388910506
-Mbd1.1387	Mbd1	17190	LIB	1387	0.200901765	0.042339934	0.359463595
-Mbd1.1856	Mbd1	17190	LIB	1856	0.078750031	0.010875476	0.146624585
-Mbd1.2237	Mbd1	17190	LIB	2237	0.145222056	0.013529275	0.276914837
-Mbd2.938	Mbd2	17191	LIB	938	0.033554608	0	0.067109216
-Mbd2.1117	Mbd2	17191	LIB	1117	0.276620876	0.447187977	0.106053776
-Mbd2.1545	Mbd2	17191	LIB	1545	0.103798129	0.202524797	0.005071462
-Mbd2.1763	Mbd2	17191	LIB	1763	0.028187951	0.001406376	0.054969526
-Mbd2.1823	Mbd2	17191	LIB	1823	0.414679837	0.282276488	0.547083186
-Mbd3.579	Mbd3	17192	LIB	579	0.039006515	0.011331445	0.066681584
-Mbd3.1147	Mbd3	17192	LIB	1147	0.132003104	0.132045515	0.131960693
-Mbd3.1354	Mbd3	17192	LIB	1354	0.036617996	0.036774807	0.036461185
-Mbd3.1452	Mbd3	17192	LIB	1452	0.87003635	1.544545602	0.195527097
-Mbd3.1551	Mbd3	17192	LIB	1551	0.141265139	0.281803323	0.000726956
-Mbd4.434	Mbd4	17193	LIB	434	0.717498316	0.023598072	1.411398561
-Mbd4.1027	Mbd4	17193	LIB	1027	0.150955677	0.221333433	0.080577921
-Mbd4.3297	Mbd4	17193	LIB	3297	0.653742815	0.838148831	0.469336798
-Mbd4.3541	Mbd4	17193	LIB	3541	0.419652469	0.667150846	0.172154092
-Mds1.87	Mds1	17251	LIB	87	0.048096175	0.003971464	0.092220886
-Mds1.651	Mds1	17251	LIB	651	0.319940409	0.13257804	0.507302777
-Mds1.764	Mds1	17251	LIB	764	0.033157893	0.001919102	0.064396684
-Mds1.874	Mds1	17251	LIB	874	0.793188133	1.077433351	0.508942915
-Mecp2.1627	Mecp2	17257	LIB	1627	0.158179087	0.277250113	0.039108062
-Mecp2.2287	Mecp2	17257	LIB	2287	0.784008604	0.547153313	1.020863896
-Mecp2.5438	Mecp2	17257	LIB	5438	0.36095926	0.389780357	0.332138162
-Mecp2.7745	Mecp2	17257	LIB	7745	0.037865771	0.010600201	0.065131342
-Men1.219	Men1	17283	LIB	219	0.122260163	0.184664749	0.059855578
-Men1.228	Men1	17283	LIB	228	0	0	0
-Men1.1457	Men1	17283	LIB	1457	0.029537974	0.059075949	0
-Men1.2310	Men1	17283	LIB	2310	0	0	0
-Men1.2707	Men1	17283	LIB	2707	0.081531892	0	0.163063784
-Mettl8.846	Mettl8	228019	LIB	846	1.673269703	2.111991617	1.234547788
-Mettl8.1184	Mettl8	228019	LIB	1184	0.530893217	0.727875059	0.333911375
-Mettl8.1353	Mettl8	228019	LIB	1353	0.232238461	0.281751288	0.182725634
-Mettl8.1914	Mettl8	228019	LIB	1914	0.286619482	0.004971898	0.568267067
-Mettl8.1990	Mettl8	228019	LIB	1990	0.061709694	0.006313275	0.117106114
-Mgmt.384	Mgmt	17314	LIB	384	0.090639202	0.001580492	0.179697912
-Mgmt.412	Mgmt	17314	LIB	412	5.939776926	4.372746171	7.506807681
-Mgmt.433	Mgmt	17314	LIB	433	0.561261701	0.568160783	0.554362619
-Mgmt.672	Mgmt	17314	LIB	672	0.019081112	0.035102041	0.003060184
-Mgmt.730	Mgmt	17314	LIB	730	0.209668367	0.252318376	0.167018358
-Mll1.4195	Mll1	214162	LIB	4195	0.205418371	0.28092254	0.129914202
-Mll1.11050	Mll1	214162	LIB	11050	0.091881752	0.041176728	0.142586776
-Mll1.13303	Mll1	214162	LIB	13303	NA	NA	NA
-Mll1.16168	Mll1	214162	LIB	16168	0.101967298	0.1481428	0.055791796
-Mll2.4285	Mll2	381022	LIB	4285	2.378116941	2.670245399	2.085988484
-Mll2.5430	Mll2	381022	LIB	5430	0.42815757	0.457258743	0.399056397
-Mll2.6153	Mll2	381022	LIB	6153	4.914842828	4.14081359	5.688872067
-Mll2.11374	Mll2	381022	LIB	11374	15.43389955	22.53070605	8.337093044
-Mll2.12943	Mll2	381022	LIB	12943	7.90198211	4.957801222	10.846163
-Mll3.1099	Mll3	231051	LIB	1099	2.088422368	3.689806678	0.487038058
-Mll3.2993	Mll3	231051	LIB	2993	0.681144071	0.610359065	0.751929076
-Mll3.5304	Mll3	231051	LIB	5304	0	0	0
-Mll3.6232	Mll3	231051	LIB	6232	1.804491278	2.920727522	0.688255034
-Mll3.15396	Mll3	231051	LIB	15396	5.053664383	7.673024929	2.434303837
-Morf4l1.281	Morf4l1	21761	LIB	281	0.139995763	0.248305961	0.031685564
-Morf4l1.603	Morf4l1	21761	LIB	603	0.031392948	0.042246873	0.020539024
-Morf4l1.639	Morf4l1	21761	LIB	639	0.11593131	0.140696498	0.091166122
-Morf4l1.1034	Morf4l1	21761	LIB	1034	0.008070115	0.005876667	0.010263563
-Morf4l1.1245	Morf4l1	21761	LIB	1245	0.355326987	0.511142363	0.199511612
-Mta1.213	Mta1	116870	LIB	213	0	0	0
-Mta1.1003	Mta1	116870	LIB	1003	0.371959696	0.15191828	0.592001111
-Mta1.1053	Mta1	116870	LIB	1053	0.101226426	0.097185681	0.10526717
-Mta1.1147	Mta1	116870	LIB	1147	0.884542293	0.609151329	1.159933256
-Mta1.1363	Mta1	116870	LIB	1363	NA	NA	NA
-Mta2.511	Mta2	23942	LIB	511	0.027716689	0.003469469	0.05196391
-Mta2.924	Mta2	23942	LIB	924	0.015603346	0.021342134	0.009864558
-Mta2.1284	Mta2	23942	LIB	1284	0.263205121	0.432928311	0.093481932
-Mta2.2013	Mta2	23942	LIB	2013	NA	NA	NA
-Mta3.222	Mta3	116871	LIB	222	0	0	0
-Mta3.553	Mta3	116871	LIB	553	0.065665497	0.003378664	0.127952329
-Mta3.1523	Mta3	116871	LIB	1523	0.610472449	0.857285113	0.363659784
-Mta3.1663	Mta3	116871	LIB	1663	0.067934747	0.118514248	0.017355245
-Myst1.643	Myst1	67773	LIB	643	0	0	0
-Myst1.724	Myst1	67773	LIB	724	0.379083512	0.089139878	0.669027146
-Myst1.1250	Myst1	67773	LIB	1250	0	0	0
-Myst1.1302	Myst1	67773	LIB	1302	0.125921699	0.044815645	0.207027753
-Myst2.176	Myst2	217127	LIB	176	0.973337724	1.441661409	0.505014039
-Myst2.507	Myst2	217127	LIB	507	2.531753597	2.010045335	3.053461859
-Myst2.1183	Myst2	217127	LIB	1183	0.93839873	1.308311364	0.568486097
-Myst2.3099	Myst2	217127	LIB	3099	0.192553734	0.281569343	0.103538124
-Myst3.2590	Myst3	244349	LIB	2590	0	0	0
-Myst3.3127	Myst3	244349	LIB	3127	0	0	0
-Myst3.3485	Myst3	244349	LIB	3485	0.006118881	0.012237762	0
-Myst3.4554	Myst3	244349	LIB	4554	0.999844656	0.815379706	1.184309605
-Myst3.6844	Myst3	244349	LIB	6844	0.756310595	0.374601925	1.138019266
-Myst4.3568	Myst4	54169	LIB	3568	0.170742331	0.244378552	0.097106109
-Myst4.5452	Myst4	54169	LIB	5452	1.060119091	1.491440019	0.628798162
-Myst4.6527	Myst4	54169	LIB	6527	0.17356428	0.192047589	0.15508097
-Myst4.6644	Myst4	54169	LIB	6644	2.400441106	2.029316862	2.771565351
-Nap1l1.2360	Nap1l1	53605	LIB	2360	0.319133892	0.437873007	0.200394778
-Nap1l1.2470	Nap1l1	53605	LIB	2470	2.672057204	0.893748358	4.45036605
-Nap1l1.3414	Nap1l1	53605	LIB	3414	0.391905722	0.627474398	0.156337047
-Nap1l1.3554	Nap1l1	53605	LIB	3554	0.112275278	0.113553114	0.110997442
-Nap1l2.819	Nap1l2	17954	LIB	819	2.125995207	0.800219962	3.451770452
-Nap1l2.1093	Nap1l2	17954	LIB	1093	0.088819529	0.018720495	0.158918562
-Nap1l2.1180	Nap1l2	17954	LIB	1180	6.48E-05	0.000129517	0
-Nap1l2.1695	Nap1l2	17954	LIB	1695	0.088807945	0.029942389	0.147673502
-Nap1l2.1750	Nap1l2	17954	LIB	1750	0.099698624	0.171510367	0.027886881
-Nap1l3.743	Nap1l3	54561	LIB	743	2.253593603	3.057823725	1.449363481
-Nap1l3.779	Nap1l3	54561	LIB	779	30.3934439	42.83344355	17.95344425
-Nap1l3.1969	Nap1l3	54561	LIB	1969	0.056225371	0.040622407	0.071828335
-Nap1l3.2063	Nap1l3	54561	LIB	2063	0.055599264	0.110335466	0.000863061
-Nap1l3.2498	Nap1l3	54561	LIB	2498	0.006560346	0.00966944	0.003451251
-Ncoa3.1032	Ncoa3	17979	LIB	1032	0.541947489	0.372010693	0.711884285
-Ncoa3.3669	Ncoa3	17979	LIB	3669	0.686557747	0.328572238	1.044543256
-Ncoa3.3815	Ncoa3	17979	LIB	3815	0.059493377	0	0.118986753
-Ncoa3.3885	Ncoa3	17979	LIB	3885	0.036495879	0.000121183	0.072870575
-Ncoa3.7494	Ncoa3	17979	LIB	7494	0.119249564	0.004346476	0.234152652
-Nr0b2.381	Nr0b2	23957	LIB	381	0.040594882	0.000521558	0.080668205
-Nr0b2.534	Nr0b2	23957	LIB	534	0.29750152	0.120015301	0.474987739
-Nr0b2.558	Nr0b2	23957	LIB	558	0.120666479	0.118932039	0.122400919
-Nr0b2.1023	Nr0b2	23957	LIB	1023	0.745556882	1.138253809	0.352859956
-Nr0b2.1068	Nr0b2	23957	LIB	1068	1.157353909	1.693199276	0.621508541
-Nsd1.2795	Nsd1	18193	LIB	2795	NA	NA	NA
-Nsd1.5598	Nsd1	18193	LIB	5598	0.586999136	0.521905831	0.652092442
-Nsd1.5640	Nsd1	18193	LIB	5640	0.006176289	0.000922834	0.011429745
-Nsd1.11634	Nsd1	18193	LIB	11634	0.35901654	0.04608508	0.671947999
-Padi4.295	Padi4	18602	LIB	295	0.140719956	0.258960573	0.022479339
-Padi4.1042	Padi4	18602	LIB	1042	0.902821311	0.530879713	1.274762908
-Padi4.1058	Padi4	18602	LIB	1058	0.458948236	0.358981494	0.558914978
-Padi4.1914	Padi4	18602	LIB	1914	0.242089806	0.484052223	0.000127389
-Padi4.2336	Padi4	18602	LIB	2336	0.062117231	0.059119919	0.065114542
-Parp1.1124	Parp1	11545	LIB	1124	0.210888138	0.367549038	0.054227238
-Parp1.1623	Parp1	11545	LIB	1623	0.104470818	0.188126755	0.02081488
-Parp1.2887	Parp1	11545	LIB	2887	0.892550544	0.316455696	1.468645392
-Parp1.3789	Parp1	11545	LIB	3789	0.015223099	0.029524865	0.000921332
-Parp1.3790	Parp1	11545	LIB	3790	0.362609031	0.342329793	0.382888269
-Parp2.574	Parp2	11546	LIB	574	0.006105603	0.012211205	0
-Parp2.905	Parp2	11546	LIB	905	0.247891643	0.495783286	0
-Parp2.946	Parp2	11546	LIB	946	0.053243848	0.106487696	0
-Parp2.1006	Parp2	11546	LIB	1006	1.662743561	1.577856302	1.74763082
-Parp2.1429	Parp2	11546	LIB	1429	0.168234787	0.308182513	0.028287061
-Parp2.1677	Parp2	11546	LIB	1677	0.030777532	0.017032993	0.04452207
-Pax5.154	Pax5	18507	LIB	154	0.16139052	0.235338822	0.087442219
-Pax5.328	Pax5	18507	LIB	328	0.39397106	0.498357756	0.289584364
-Pax5.601	Pax5	18507	LIB	601	0.048479251	0.024589675	0.072368828
-Pax5.852	Pax5	18507	LIB	852	9.678858441	7.766500178	11.5912167
-Pax5.914	Pax5	18507	LIB	914	0.152719984	0.030076142	0.275363825
-Paxip1.3203	Paxip1	55982	LIB	3203	0.187420804	0.303786616	0.071054993
-Paxip1.3451	Paxip1	55982	LIB	3451	3.865093664	3.578045861	4.152141468
-Paxip1.3562	Paxip1	55982	LIB	3562	0.722329293	0.613098514	0.831560072
-Paxip1.3670	Paxip1	55982	LIB	3670	5.124811105	9.197264873	1.052357337
-Pcgf2.507	Pcgf2	22658	LIB	507	0.35115	0.32717803	0.375121969
-Pcgf2.690	Pcgf2	22658	LIB	690	0.084288102	0.160556564	0.00801964
-Pcgf2.801	Pcgf2	22658	LIB	801	0.09993849	0.068596738	0.131280242
-Pcgf2.982	Pcgf2	22658	LIB	982	0.444925531	0.384459989	0.505391072
-Pcgf2.1013	Pcgf2	22658	LIB	1013	0.090092787	5.67E-05	0.180128878
-Pcmt1.619	Pcmt1	18537	LIB	619	1.638746981	2.371052632	0.90644133
-Pcmt1.620	Pcmt1	18537	LIB	620	0.066119686	0.000258465	0.131980907
-Pcmt1.840	Pcmt1	18537	LIB	840	27.42358533	24.71543731	30.13173335
-Pcmt1.946	Pcmt1	18537	LIB	946	0.678912333	0.407078398	0.950746269
-Pcmt1.1259	Pcmt1	18537	LIB	1259	0.610136449	0.807828401	0.412444497
-Pcna.566	Pcna	18538	PC	566	0.013756331	0.021430795	0.006081866
-Pcna.1186	Pcna	18538	PC	1186	0	0	0
-Phf1.561	Phf1	21652	LIB	561	0.571926578	1.105404769	0.038448387
-Phf1.637	Phf1	21652	LIB	637	0.33142531	0.459700889	0.203149731
-Phf1.1098	Phf1	21652	LIB	1098	0.118527608	0.184246062	0.052809154
-Phf1.2400	Phf1	21652	LIB	2400	0.178047503	0.204710012	0.151384993
-Phf2.1851	Phf2	18676	LIB	1851	0.281793921	0.46524031	0.098347533
-Phf2.3668	Phf2	18676	LIB	3668	0.352946923	0.001776199	0.704117647
-Phf2.5132	Phf2	18676	LIB	5132	1.021354121	0.675807289	1.366900952
-Phf2.5166	Phf2	18676	LIB	5166	1.690348646	0.566009654	2.814687638
-Phf8.1420	Phf8	320595	LIB	1420	0.539886389	0.513086274	0.566686504
-Phf8.1984	Phf8	320595	LIB	1984	0.090594691	0.06110417	0.120085213
-Phf8.2131	Phf8	320595	LIB	2131	0.020983494	0.041486603	0.000480384
-Polr2b.489	Polr2b	231329	PC	489	0	0	0
-Polr2b.2176	Polr2b	231329	PC	2176	3.53E-05	7.06E-05	0
-Ppargc1a.669	Ppargc1a	19017	LIB	669	0.538610763	0.908737392	0.168484134
-Ppargc1a.831	Ppargc1a	19017	LIB	831	NA	NA	NA
-Ppargc1a.1269	Ppargc1a	19017	LIB	1269	0.408904844	0.436043305	0.381766382
-Ppargc1a.1500	Ppargc1a	19017	LIB	1500	0.229797051	0.203566341	0.256027762
-Prdm1.711	Prdm1	12142	LIB	711	0.050370956	0.017908875	0.082833036
-Prdm1.862	Prdm1	12142	LIB	862	0.127106083	0.093023256	0.161188911
-Prdm1.919	Prdm1	12142	LIB	919	0.064288331	0.02643779	0.102138872
-Prdm1.2964	Prdm1	12142	LIB	2964	0.090658195	0.169964956	0.011351434
-Prdm1.3709	Prdm1	12142	LIB	3709	0.964704579	0.430668605	1.498740554
-Prdm10.318	Prdm10	382066	LIB	318	0.06919639	0.042373324	0.096019455
-Prdm10.1130	Prdm10	382066	LIB	1130	0.161461455	0.167124645	0.155798265
-Prdm10.1348	Prdm10	382066	LIB	1348	0.121409823	0.178588808	0.064230838
-Prdm10.2613	Prdm10	382066	LIB	2613	0.275005354	0.550010709	0
-Prdm11.1844	Prdm11	100042784	LIB	1844	0.049836641	0.003384095	0.096289187
-Prdm11.2306	Prdm11	100042784	LIB	2306	0.106674086	0.187523208	0.025824964
-Prdm11.3215	Prdm11	100042784	LIB	3215	0.248260853	0.357676324	0.138845382
-Prdm11.3216	Prdm11	100042784	LIB	3216	0.162689304	0.102281495	0.223097113
-Prdm12.481	Prdm12	381359	LIB	481	0.121026312	9.03E-05	0.241962372
-Prdm12.603	Prdm12	381359	LIB	603	0.11654652	0.146549398	0.086543642
-Prdm12.1421	Prdm12	381359	LIB	1421	0.036882594	0.001164353	0.072600834
-Prdm12.2351	Prdm12	381359	LIB	2351	0.862186131	0.987938749	0.736433513
-Prdm13.554	Prdm13	230025	LIB	554	0.060698903	0.02212727	0.099270536
-Prdm13.2613	Prdm13	230025	LIB	2613	5.270386453	3.099350703	7.441422202
-Prdm13.2702	Prdm13	230025	LIB	2702	0.521784232	0	1.043568465
-Prdm13.2828	Prdm13	230025	LIB	2828	0.075151234	0.112102387	0.038200081
-Prdm13.2936	Prdm13	230025	LIB	2936	0.269317079	0.20276676	0.335867398
-Prdm14.530	Prdm14	383491	LIB	530	0.405412499	0.39411959	0.416705408
-Prdm14.1756	Prdm14	383491	LIB	1756	0.005945122	0	0.011890244
-Prdm14.1934	Prdm14	383491	LIB	1934	0.293485392	0.527073733	0.059897052
-Prdm14.2271	Prdm14	383491	LIB	2271	0.111037316	0.097569355	0.124505277
-Prdm14.2348	Prdm14	383491	LIB	2348	0.492448295	0.042176871	0.94271972
-Prdm15.958	Prdm15	114604	LIB	958	0.98252896	1.932489451	0.032568468
-Prdm15.1034	Prdm15	114604	LIB	1034	0.004062756	0.003733333	0.004392179
-Prdm15.1690	Prdm15	114604	LIB	1690	0.524906994	0.429446747	0.620367241
-Prdm15.1796	Prdm15	114604	LIB	1796	0.174355348	0.183572542	0.165138154
-Prdm15.2734	Prdm15	114604	LIB	2734	0.038957255	0.003943577	0.073970934
-Prdm16.680	Prdm16	70673	LIB	680	0.533914395	0.660762545	0.407066246
-Prdm16.5683	Prdm16	70673	LIB	5683	0.096716361	0.180946552	0.01248617
-Prdm16.8212	Prdm16	70673	LIB	8212	NA	NA	NA
-Prdm16.8363	Prdm16	70673	LIB	8363	0.430720448	0.248793956	0.61264694
-Prdm16.8571	Prdm16	70673	LIB	8571	2.329170058	2.550566982	2.107773134
-Prdm2.1020	Prdm2	110593	LIB	1020	0.153596644	0.259297344	0.047895945
-Prdm2.4191	Prdm2	110593	LIB	4191	0.559676498	0.502441293	0.616911704
-Prdm2.4655	Prdm2	110593	LIB	4655	NA	NA	NA
-Prdm2.4956	Prdm2	110593	LIB	4956	0.090352843	0.160106435	0.020599251
-Prdm2.5781	Prdm2	110593	LIB	5781	0.2845147	0.353298153	0.215731247
-Prdm4.1943	Prdm4	72843	LIB	1943	0.115287664	0.047414054	0.183161274
-Prdm4.2535	Prdm4	72843	LIB	2535	0.085408022	0.000193199	0.170622844
-Prdm4.3139	Prdm4	72843	LIB	3139	0.001128668	0	0.002257336
-Prdm4.3391	Prdm4	72843	LIB	3391	0.069371374	0.05967095	0.079071797
-Prdm4.3667	Prdm4	72843	LIB	3667	NA	NA	NA
-Prdm5.908	Prdm5	70779	LIB	908	0.149313429	0.128342246	0.170284612
-Prdm5.984	Prdm5	70779	LIB	984	0.413409055	0.622305737	0.204512373
-Prdm5.1353	Prdm5	70779	LIB	1353	1.643969827	2.094062103	1.193877551
-Prdm5.2148	Prdm5	70779	LIB	2148	0.648213784	0.715798492	0.580629076
-Prdm6.1018	Prdm6	225518	LIB	1018	0.009633756	0.011159403	0.008108108
-Prdm6.1790	Prdm6	225518	LIB	1790	0.123211194	0.098809823	0.147612565
-Prdm6.1823	Prdm6	225518	LIB	1823	0.328175562	0.377128018	0.279223106
-Prdm6.1839	Prdm6	225518	LIB	1839	0.201249487	0.337440758	0.065058216
-Prdm8.2290	Prdm8	77630	LIB	2290	0.000542104	0.00048216	0.000602047
-Prdm8.3042	Prdm8	77630	LIB	3042	3.233747051	5.976620158	0.490873944
-Prdm8.3048	Prdm8	77630	LIB	3048	0.640755782	1.166720727	0.114790837
-Prdm8.3062	Prdm8	77630	LIB	3062	0.361793005	0.256726293	0.466859717
-Prdm9.77	Prdm9	213389	LIB	77	0.401141561	0.283516221	0.518766901
-Prdm9.496	Prdm9	213389	LIB	496	0.222497616	0.078468537	0.366526695
-Prdm9.1838	Prdm9	213389	LIB	1838	0.302877526	0.400302009	0.205453043
-Prkaa1.145	Prkaa1	105787	LIB	145	0.14165733	0.1690104	0.114304261
-Prkaa1.1981	Prkaa1	105787	LIB	1981	0.019533353	0.019407151	0.019659554
-Prkaa1.3080	Prkaa1	105787	LIB	3080	NA	NA	NA
-Prkaa1.3635	Prkaa1	105787	LIB	3635	3.189719542	4.278249106	2.101189977
-Prkaa1.3954	Prkaa1	105787	LIB	3954	0.013169577	0	0.026339154
-Prkaa1.4596	Prkaa1	105787	LIB	4596	0.034088344	0.058964593	0.009212095
-Prkaa2.2299	Prkaa2	108079	LIB	2299	0.004331754	0.000484027	0.008179481
-Prkaa2.2748	Prkaa2	108079	LIB	2748	0.340786503	0.362280234	0.319292772
-Prkaa2.4825	Prkaa2	108079	LIB	4825	NA	NA	NA
-Prkaa2.6172	Prkaa2	108079	LIB	6172	0.020265668	0	0.040531335
-Prkaa2.6849	Prkaa2	108079	LIB	6849	0.135065674	0.072316173	0.197815176
-Prkcd.161	Prkcd	18753	LIB	161	0.179448269	0.099882029	0.259014509
-Prkcd.441	Prkcd	18753	LIB	441	0.327507015	0.001459854	0.653554175
-Prkcd.707	Prkcd	18753	LIB	707	0.664294206	1.071999112	0.2565893
-Prkcd.1389	Prkcd	18753	LIB	1389	1.255652224	0.641311475	1.869992973
-Prmt1.243	Prmt1	15469	LIB	243	0.110664823	0.120254845	0.101074802
-Prmt1.264	Prmt1	15469	LIB	264	0.272777523	0.382384883	0.163170163
-Prmt1.630	Prmt1	15469	LIB	630	1.328852347	1.764027294	0.8936774
-Prmt1.1014	Prmt1	15469	LIB	1014	0.484140888	0.638219895	0.330061882
-Prmt2.151	Prmt2	15468	LIB	151	0.031631618	0.037750897	0.025512338
-Prmt2.154	Prmt2	15468	LIB	154	0.973162231	1.211030345	0.735294118
-Prmt2.1066	Prmt2	15468	LIB	1066	9.18E-05	0.000183688	0
-Prmt2.1067	Prmt2	15468	LIB	1067	0.815640774	0.654386731	0.976894818
-Prmt3.502	Prmt3	71974	LIB	502	0.157500935	0.315001871	0
-Prmt3.814	Prmt3	71974	LIB	814	4.89E-05	0	9.79E-05
-Prmt3.838	Prmt3	71974	LIB	838	3.559311442	4.211350585	2.907272299
-Prmt3.985	Prmt3	71974	LIB	985	0.274535697	0.423260006	0.125811388
-Prmt3.1839	Prmt3	71974	LIB	1839	0.113816928	0.148898678	0.078735178
-Prmt5.56	Prmt5	27374	LIB	56	0.778904793	0.453405018	1.104404568
-Prmt5.266	Prmt5	27374	LIB	266	0.201764199	0.173979378	0.22954902
-Prmt5.2152	Prmt5	27374	LIB	2152	0.126875652	0.076575692	0.177175612
-Prmt5.2293	Prmt5	27374	LIB	2293	2.188455879	0.469499821	3.907411937
-Prmt6.247	Prmt6	99890	LIB	247	0.033732942	0.000853242	0.066612642
-Prmt6.1493	Prmt6	99890	LIB	1493	0.134310673	0.232186732	0.036434613
-Prmt6.1983	Prmt6	99890	LIB	1983	0.154846836	0.167501928	0.142191745
-Prmt6.2355	Prmt6	99890	LIB	2355	0.50072786	0.541981695	0.459474025
-Prmt7.23	Prmt7	214572	LIB	23	0.009433344	0.004819277	0.01404741
-Prmt7.45	Prmt7	214572	LIB	45	0.543933929	0.518786922	0.569080936
-Prmt7.88	Prmt7	214572	LIB	88	0.080612502	0.04869904	0.112525964
-Prmt7.1284	Prmt7	214572	LIB	1284	0.06501016	0.126209284	0.003811036
-Prmt7.2135	Prmt7	214572	LIB	2135	0.23497578	0.386599091	0.083352468
-Prmt8.302	Prmt8	381813	LIB	302	0.244600451	0.198269736	0.290931167
-Prmt8.455	Prmt8	381813	LIB	455	0.59669119	0.802821189	0.390561191
-Prmt8.667	Prmt8	381813	LIB	667	0.045662786	0.087305569	0.004020002
-Prmt8.1854	Prmt8	381813	LIB	1854	0.108178455	0.06973876	0.146618151
-Psip1.763	Psip1	101739	LIB	763	0.008304892	0	0.016609784
-Psip1.1311	Psip1	101739	LIB	1311	0	0	0
-Psip1.1596	Psip1	101739	LIB	1596	0.059717843	0.087169563	0.032266123
-Psip1.2474	Psip1	101739	LIB	2474	0.006237689	0.012475378	0
-Psip1.2652	Psip1	101739	LIB	2652	0.06194056	0.10699453	0.016886591
-Rbbp4.2088	Rbbp4	19646	LIB	2088	0.193789327	0.126048165	0.261530489
-Rbbp4.2174	Rbbp4	19646	LIB	2174	0.005813953	0	0.011627907
-Rbbp4.2511	Rbbp4	19646	LIB	2511	0.928220759	1.004589667	0.851851852
-Rbbp4.3753	Rbbp4	19646	LIB	3753	0.073360623	0.135745027	0.010976218
-Rbbp5.1634	Rbbp5	213464	LIB	1634	1.015990856	1.156510409	0.875471303
-Rbbp5.2248	Rbbp5	213464	LIB	2248	0.000789875	0.00145743	0.00012232
-Rbbp5.2655	Rbbp5	213464	LIB	2655	0.121958567	0.170557717	0.073359417
-Rbbp5.2974	Rbbp5	213464	LIB	2974	1.399302063	1.445902998	1.352701127
-Renilla.713	Renilla	Luciferase	NC	713	1.666788004	1.533762916	1.799813091
-Ring1.260	Ring1	19763	LIB	260	0.286061741	0.026611473	0.54551201
-Ring1.669	Ring1	19763	LIB	669	0.165118469	0.170742026	0.159494912
-Ring1.1034	Ring1	19763	LIB	1034	0.180669238	0.016304348	0.345034127
-Rnf2.1856	Rnf2	19821	LIB	1856	0.673388184	0.833867094	0.512909274
-Rnf2.2203	Rnf2	19821	LIB	2203	0.954595303	0.850564925	1.05862568
-Rnf2.2538	Rnf2	19821	LIB	2538	0.837959761	0.541602515	1.134317006
-Rnf2.2809	Rnf2	19821	LIB	2809	0.187347204	0.081992104	0.292702304
-Rnf2.2875	Rnf2	19821	LIB	2875	0.546987675	0.692397599	0.401577752
-Rnf20.420	Rnf20	109331	LIB	420	0.063920224	0.054351697	0.073488751
-Rnf20.948	Rnf20	109331	LIB	948	0.278768206	0.423430663	0.134105749
-Rnf20.1295	Rnf20	109331	LIB	1295	0.000109004	0	0.000218007
-Rnf20.3244	Rnf20	109331	LIB	3244	NA	NA	NA
-Rnf20.3277	Rnf20	109331	LIB	3277	0.459938908	0.803347787	0.11653003
-Rnf20.3718	Rnf20	109331	LIB	3718	1.136821022	1.414336918	0.859305126
-Rpa1.1620	Rpa1	68275	PC	1620	0.007210873	0.000351973	0.014069774
-Rpa3.276	Rpa3	68240	PC	278	7.32E-05	0.000111564	3.48E-05
-Rpa3.455	Rpa3	68240	PC	457	0.018174308	0.02069689	0.015651726
-Rpa3.561	Rpa3	68240	PC	561	0.00476048	0.002574918	0.006946042
-Satb1.710	Satb1	20230	LIB	710	0.161960667	0.323389702	0.000531632
-Satb1.1401	Satb1	20230	LIB	1401	0.392569667	0.3563288	0.428810533
-Satb1.1478	Satb1	20230	LIB	1478	0.24003152	0.473695747	0.006367292
-Satb1.1709	Satb1	20230	LIB	1709	0.193635318	0.075057818	0.312212817
-Satb1.2566	Satb1	20230	LIB	2566	0.193845463	0.035309973	0.352380952
-Setd1a.119	Setd1a	233904	LIB	119	0.107452217	0.170620438	0.044283995
-Setd1a.388	Setd1a	233904	LIB	388	0.608381477	0.653331355	0.5634316
-Setd1a.643	Setd1a	233904	LIB	643	1.521441453	1.691804708	1.351078197
-Setd1a.5859	Setd1a	233904	LIB	5859	0.797831182	0.900645478	0.695016886
-Setd1b.3553	Setd1b	208043	LIB	3553	8.23E-05	0	0.0001646
-Setd1b.3557	Setd1b	208043	LIB	3557	0.18069148	0.180119102	0.181263858
-Setd1b.4520	Setd1b	208043	LIB	4520	0.199934074	0.05129672	0.348571429
-Setd1b.4522	Setd1b	208043	LIB	4522	0.003342509	0	0.006685018
-Setd1b.4699	Setd1b	208043	LIB	4699	0.137405083	0.097939189	0.176870978
-Setd2.182	Setd2	235626	LIB	182	0.040179039	0.047492416	0.032865662
-Setd2.1467	Setd2	235626	LIB	1467	0.00017313	0	0.00034626
-Setd2.1785	Setd2	235626	LIB	1785	0.038294803	0.027488932	0.049100673
-Setd2.3632	Setd2	235626	LIB	3632	0.377349359	0.44562685	0.309071868
-Setd2.4051	Setd2	235626	LIB	4051	0	0	0
-Setd3.795	Setd3	52690	LIB	795	0.126767545	0.027322404	0.226212687
-Setd3.1496	Setd3	52690	LIB	1496	NA	NA	NA
-Setd3.2395	Setd3	52690	LIB	2395	0.012222377	0	0.024444755
-Setd4.506	Setd4	224440	LIB	506	0.001721296	0.001794728	0.001647864
-Setd4.1308	Setd4	224440	LIB	1308	2.55E-05	5.10E-05	0
-Setd4.1517	Setd4	224440	LIB	1517	0	0	0
-Setd7.4328	Setd7	73251	LIB	4328	0.79628381	1.371309831	0.22125779
-Setd7.5317	Setd7	73251	LIB	5317	0.441117913	0.586184524	0.296051303
-Setd7.5342	Setd7	73251	LIB	5342	0.143929674	0.043706114	0.244153234
-Setd7.5940	Setd7	73251	LIB	5940	NA	NA	NA
-Setd7.7009	Setd7	73251	LIB	7009	0.066151971	0.049381188	0.082922753
-Setd8.2578	Setd8	67956	LIB	2578	0.189731658	0.000972526	0.37849079
-Setd8.2622	Setd8	67956	LIB	2622	0.411566348	0.623313229	0.199819467
-Setd8.2632	Setd8	67956	LIB	2632	1.643161397	2.493088617	0.793234176
-Setdb1.1145	Setdb1	84505	LIB	1145	0.517510269	0.470614035	0.564406503
-Setdb1.1925	Setdb1	84505	LIB	1925	0.086579742	0	0.173159485
-Setdb1.2174	Setdb1	84505	LIB	2174	0.146093257	0.000108015	0.292078499
-Setdb1.3684	Setdb1	84505	LIB	3684	0.010401671	8.66E-05	0.02071677
-Setdb2.809	Setdb2	239122	LIB	809	1.391206827	2.779885057	0.002528597
-Setdb2.810	Setdb2	239122	LIB	810	1.190095337	0.963319847	1.416870827
-Setdb2.990	Setdb2	239122	LIB	990	0.079364105	0.021533706	0.137194504
-Setdb2.1417	Setdb2	239122	LIB	1417	0.34737866	0.393661661	0.30109566
-Setmar.1193	Setmar	74729	LIB	1193	0.292843192	0.358163209	0.227523174
-Setmar.1195	Setmar	74729	LIB	1195	0.162091025	0.135760257	0.188421792
-Setmar.1589	Setmar	74729	LIB	1589	64.11298219	52.14726514	76.07869924
-Sfmbt1.868	Sfmbt1	54650	LIB	868	1.013294698	1.206846418	0.819742977
-Sfmbt1.1345	Sfmbt1	54650	LIB	1345	0.008587566	0.010476801	0.006698332
-Sfmbt1.1802	Sfmbt1	54650	LIB	1802	1.004772904	0.72139738	1.288148429
-Sfmbt1.2018	Sfmbt1	54650	LIB	2018	0.26726547	0.475359343	0.059171598
-Sfmbt1.2421	Sfmbt1	54650	LIB	2421	0.075539295	0.001624805	0.149453785
-Sfmbt2.602	Sfmbt2	353282	LIB	602	0.281181984	0.520202721	0.042161246
-Sfmbt2.3592	Sfmbt2	353282	LIB	3592	0.082878502	0.005644644	0.16011236
-Sfmbt2.5673	Sfmbt2	353282	LIB	5673	0.134401376	0.019676674	0.249126078
-Sin3a.531	Sin3a	20466	LIB	531	0	0	0
-Sin3a.3537	Sin3a	20466	LIB	3537	0.024340683	0	0.048681366
-Sin3a.3559	Sin3a	20466	LIB	3559	1.728939777	2.831898734	0.62598082
-Sin3a.4729	Sin3a	20466	LIB	4729	0	0	0
-Sin3b.188	Sin3b	20467	LIB	188	0.042293799	0.084587598	0
-Sin3b.326	Sin3b	20467	LIB	326	1.438726271	2.275190706	0.602261836
-Sin3b.338	Sin3b	20467	LIB	338	0.105590062	0	0.211180124
-Sin3b.381	Sin3b	20467	LIB	381	0.134926536	0.248162305	0.021690768
-Sin3b.475	Sin3b	20467	LIB	475	0.639579924	1.118636662	0.160523187
-Sirt1.688	Sirt1	93759	LIB	688	1.451209242	1.979805805	0.922612678
-Sirt1.1708	Sirt1	93759	LIB	1708	0.631165203	0.733237638	0.529092768
-Sirt1.1779	Sirt1	93759	LIB	1779	0.436869096	0.336818563	0.536919629
-Sirt1.2191	Sirt1	93759	LIB	2191	1.729713563	2.528467711	0.930959415
-Sirt2.735	Sirt2	64383	LIB	735	0.147707432	0.003062938	0.292351926
-Sirt2.1418	Sirt2	64383	LIB	1418	0.131476192	0.093366665	0.169585719
-Sirt2.1460	Sirt2	64383	LIB	1460	0.276894538	0.290329505	0.26345957
-Sirt2.1600	Sirt2	64383	LIB	1600	0.023729675	0.026015228	0.021444122
-Sirt3.462	Sirt3	64384	LIB	462	0.43015768	0.70883566	0.1514797
-Sirt3.869	Sirt3	64384	LIB	869	0.087373128	0.032567568	0.142178688
-Sirt3.993	Sirt3	64384	LIB	993	1.118453529	1.035942224	1.200964834
-Sirt3.1002	Sirt3	64384	LIB	1002	0.316055067	0.208823529	0.423286604
-Sirt3.1236	Sirt3	64384	LIB	1236	0.23257166	0.248811512	0.216331808
-Sirt4.105	Sirt4	75387	LIB	105	0.787448713	0.84617509	0.728722336
-Sirt4.633	Sirt4	75387	LIB	633	0.413766331	0.018150999	0.809381663
-Sirt4.1490	Sirt4	75387	LIB	1490	0.271724181	0.467032967	0.076415394
-Sirt4.1806	Sirt4	75387	LIB	1806	0.211146978	0.364117918	0.058176038
-Sirt5.586	Sirt5	68346	LIB	586	0.04315097	0.061098763	0.025203178
-Sirt5.1032	Sirt5	68346	LIB	1032	NA	NA	NA
-Sirt5.1219	Sirt5	68346	LIB	1219	1.159282043	1.459821841	0.858742245
-Sirt5.1290	Sirt5	68346	LIB	1290	0.148949431	0.165555092	0.132343769
-Sirt6.83	Sirt6	50721	LIB	83	0.036022476	0.05303979	0.019005162
-Sirt6.421	Sirt6	50721	LIB	421	0.000122991	0	0.000245982
-Sirt6.937	Sirt6	50721	LIB	937	0.232027633	0.160600291	0.303454974
-Sirt6.1609	Sirt6	50721	LIB	1609	0.364602844	0.086260111	0.642945578
-Sirt7.841	Sirt7	209011	LIB	841	0	0	0
-Sirt7.844	Sirt7	209011	LIB	844	0.221531023	0.111507818	0.331554227
-Sirt7.1238	Sirt7	209011	LIB	1238	0.21552915	0.207286174	0.223772125
-Sirt7.1604	Sirt7	209011	LIB	1604	0.118405846	0.003893381	0.232918312
-Sirt7.1677	Sirt7	209011	LIB	1677	0.451595828	0.535251456	0.367940199
-Smarca1.1401	Smarca1	93761	LIB	1401	1.153548695	1.688711584	0.618385807
-Smarca1.1430	Smarca1	93761	LIB	1430	0.46036335	0.786028584	0.134698116
-Smarca1.1613	Smarca1	93761	LIB	1613	0.11066776	0.061904944	0.159430577
-Smarca1.1893	Smarca1	93761	LIB	1893	0.213806299	0.218937644	0.208674954
-Smarca1.3418	Smarca1	93761	LIB	3418	0.607874304	1.091527057	0.124221551
-Smarca2.263	Smarca2	67155	LIB	263	0.172543567	0.178539893	0.166547241
-Smarca2.274	Smarca2	67155	LIB	274	0	0	0
-Smarca2.712	Smarca2	67155	LIB	712	0.035563959	0.003878282	0.067249636
-Smarca2.1061	Smarca2	67155	LIB	1061	0.08050899	0.120002107	0.041015873
-Smarca4.3232	Smarca4	20586	LIB	3232	0	0	0
-Smarca4.3364	Smarca4	20586	LIB	3364	0.185891845	0	0.371783689
-Smarca4.3633	Smarca4	20586	LIB	3633	0.101871507	0.169502565	0.03424045
-Smarca4.4935	Smarca4	20586	LIB	4935	0.464028994	0.638482699	0.28957529
-Smarca4.5466	Smarca4	20586	LIB	5466	0	0	0
-Smarca5.1139	Smarca5	93762	LIB	1139	39.02044459	29.48150462	48.55938456
-Smarca5.1264	Smarca5	93762	LIB	1264	0.051361802	0.102723605	0
-Smarca5.3886	Smarca5	93762	LIB	3886	2.889445252	4.275900073	1.502990431
-Smarca5.4421	Smarca5	93762	LIB	4421	0.027038126	0.047147846	0.006928406
-Smarca5.4522	Smarca5	93762	LIB	4522	1.659875833	1.301821998	2.017929668
-Smarcc2.1398	Smarcc2	68094	LIB	1398	5.667513887	8.025575273	3.309452502
-Smarcc2.1941	Smarcc2	68094	LIB	1941	0.671956498	0.125396825	1.21851617
-Smarcc2.2235	Smarcc2	68094	LIB	2235	0.277627685	0.414749573	0.140505797
-Smarcc2.2541	Smarcc2	68094	LIB	2541	0.369172133	0.397641112	0.340703153
-Smarcd1.690	Smarcd1	83797	LIB	690	0.029841397	0.009797964	0.049884831
-Smarcd1.986	Smarcd1	83797	LIB	986	0.145361327	0.246381645	0.044341009
-Smarcd1.1738	Smarcd1	83797	LIB	1738	0.763237236	1.299479167	0.226995305
-Smarcd1.1858	Smarcd1	83797	LIB	1858	0.19664493	0.30078986	0.0925
-Smarcd3.518	Smarcd3	66993	LIB	518	0.109320414	0.188431483	0.030209345
-Smarcd3.847	Smarcd3	66993	LIB	847	0.27744907	0.176790744	0.378107396
-Smarcd3.1323	Smarcd3	66993	LIB	1323	0.345474467	0.457416001	0.233532934
-Smarcd3.1591	Smarcd3	66993	LIB	1591	0.117582645	0.231035335	0.004129956
-Smarcd3.1708	Smarcd3	66993	LIB	1708	0	0	0
-Smarce1.2096	Smarce1	57376	LIB	2096	0.225624714	0.208014266	0.243235162
-Smarce1.2121	Smarce1	57376	LIB	2121	5.976009675	3.943683037	8.008336314
-Smarce1.2154	Smarce1	57376	LIB	2154	0.166161562	0.03823709	0.294086035
-Smarce1.2337	Smarce1	57376	LIB	2337	0.574918385	0.45703001	0.692806761
-Smarce1.2593	Smarce1	57376	LIB	2593	0.101831674	0.067653641	0.136009708
-Smyd1.1302	Smyd1	12180	LIB	1302	0.113264066	0.14391266	0.082615473
-Smyd1.1635	Smyd1	12180	LIB	1635	0.847881262	0.759523917	0.936238607
-Smyd1.1658	Smyd1	12180	LIB	1658	0.487657271	0.079701835	0.895612708
-Smyd2.334	Smyd2	226830	LIB	334	0.333287943	0.426382841	0.240193045
-Smyd2.640	Smyd2	226830	LIB	640	0	0	0
-Smyd2.1421	Smyd2	226830	LIB	1421	0.033647219	0.007321641	0.059972796
-Smyd2.1476	Smyd2	226830	LIB	1476	0.133552973	0.166871585	0.100234361
-Smyd3.306	Smyd3	69726	LIB	306	0.984033005	1.765638646	0.202427363
-Smyd3.438	Smyd3	69726	LIB	438	0.268051697	0.342375668	0.193727726
-Smyd3.980	Smyd3	69726	LIB	980	6.230065777	7.131274131	5.328857422
-Smyd3.1506	Smyd3	69726	LIB	1506	0	0	0
-Smyd3.2607	Smyd3	69726	LIB	2607	0.407196317	0.531783938	0.282608696
-Smyd4.693	Smyd4	319822	LIB	693	0.034680679	0	0.069361358
-Smyd4.2959	Smyd4	319822	LIB	2959	0.124362265	0.177337952	0.071386579
-Smyd4.3333	Smyd4	319822	LIB	3333	0.281233349	0.168597717	0.393868982
-Smyd4.3414	Smyd4	319822	LIB	3414	0.036082039	0.064381611	0.007782466
-Smyd4.3439	Smyd4	319822	LIB	3439	0.102705754	0.118006231	0.087405278
-Smyd5.1548	Smyd5	232187	LIB	1548	0.555290132	1.105784101	0.004796163
-Smyd5.1643	Smyd5	232187	LIB	1643	0.201223576	0.237695287	0.164751865
-Smyd5.2044	Smyd5	232187	LIB	2044	0.100536441	0	0.201072882
-Smyd5.2048	Smyd5	232187	LIB	2048	4.496682919	5.749585661	3.243780178
-Srcap.2697	Srcap	100043597	LIB	2697	0.349388033	0	0.698776065
-Srcap.3130	Srcap	100043597	LIB	3130	0.212521996	0.244648899	0.180395093
-Srcap.5342	Srcap	100043597	LIB	5342	0.052050563	0.074190594	0.029910532
-Srcap.7360	Srcap	100043597	LIB	7360	0.000185048	0.000370096	0
-Srcap.11381	Srcap	100043597	LIB	11381	0.306910194	0.366298636	0.247521752
-Ssrp1.306	Ssrp1	20833	LIB	306	0.130932283	0	0.261864566
-Ssrp1.577	Ssrp1	20833	LIB	577	0	0	0
-Ssrp1.897	Ssrp1	20833	LIB	897	0	0	0
-Ssrp1.975	Ssrp1	20833	LIB	975	0.173798872	0	0.347597744
-Ssrp1.2237	Ssrp1	20833	LIB	2237	0.516140607	0.49304499	0.539236223
-Supt16h.1672	Supt16h	114741	LIB	1672	0	0	0
-Supt16h.2037	Supt16h	114741	LIB	2037	0	0	0
-Supt16h.2827	Supt16h	114741	LIB	2827	0.254409407	0	0.508818813
-Supt16h.2999	Supt16h	114741	LIB	2999	1.544048922	1.927461878	1.160635965
-Suv39h1.496	Suv39h1	20937	LIB	496	0.00769067	0.00522541	0.010155929
-Suv39h1.1016	Suv39h1	20937	LIB	1016	0.16138236	0.206581683	0.116183036
-Suv39h1.1202	Suv39h1	20937	LIB	1202	0.443170347	0.001824633	0.884516062
-Suv39h1.1471	Suv39h1	20937	LIB	1471	0.813201059	0.763236816	0.863165302
-Suv39h1.1827	Suv39h1	20937	LIB	1827	0.001449922	0	0.002899844
-Suv39h2.1395	Suv39h2	64707	LIB	1395	1.277126142	1.595355855	0.958896428
-Suv39h2.1871	Suv39h2	64707	LIB	1871	1.121534494	0.83378821	1.409280778
-Suv39h2.2981	Suv39h2	64707	LIB	2981	0.431886028	0.596321373	0.267450683
-Suv39h2.4184	Suv39h2	64707	LIB	4184	0.175666404	0.146602132	0.204730676
-Suv420h1.1112	Suv420h1	225888	LIB	1112	0.524975639	0.491653823	0.558297455
-Suv420h1.1327	Suv420h1	225888	LIB	1327	0.116790353	0	0.233580705
-Suv420h1.3263	Suv420h1	225888	LIB	3263	0.368685154	0.493047776	0.244322531
-Suv420h1.3357	Suv420h1	225888	LIB	3357	1.324294468	2.048844691	0.599744246
-Suv420h2.287	Suv420h2	232811	LIB	287	0.022964894	0.007424692	0.038505096
-Suv420h2.686	Suv420h2	232811	LIB	686	0.11526632	0.108108108	0.122424533
-Suv420h2.825	Suv420h2	232811	LIB	825	0.001755618	0	0.003511236
-Suz12.909	Suz12	52615	LIB	909	0.039791094	0.041071615	0.038510573
-Suz12.1676	Suz12	52615	LIB	1676	0.485871904	0.850335377	0.121408431
-Suz12.1842	Suz12	52615	LIB	1842	0	0	0
-Suz12.3979	Suz12	52615	LIB	3979	0.728677324	0.747851003	0.709503645
-Suz12.4300	Suz12	52615	LIB	4300	2.273232665	3.766706979	0.779758351
-Taf1.928	Taf1	270627	LIB	928	0.422721162	0.600757627	0.244684697
-Taf1.3994	Taf1	270627	LIB	3994	2.625498891	2.982654402	2.26834338
-Taf1.5030	Taf1	270627	LIB	5030	64.36949812	5.851261461	122.8877348
-Taf1.7786	Taf1	270627	LIB	7786	0.523945504	0.14720006	0.900690947
-Taf3.1009	Taf3	209361	LIB	1009	0.630071751	0.858078928	0.402064575
-Taf3.1315	Taf3	209361	LIB	1315	0.261363856	0.00010287	0.522624842
-Taf3.1769	Taf3	209361	LIB	1769	0.29960417	0.043652785	0.555555556
-Taf3.2951	Taf3	209361	LIB	2951	0	0	0
-Taf3.3182	Taf3	209361	LIB	3182	1.204653902	1.789020893	0.620286911
-Ube2a.142	Ube2a	22209	LIB	142	0	0	0
-Ube2a.786	Ube2a	22209	LIB	786	0.120099234	0.13903066	0.101167809
-Ube2a.1206	Ube2a	22209	LIB	1206	0.144990808	0.114695126	0.17528649
-Ube2a.1411	Ube2a	22209	LIB	1411	0.060153226	0.085591229	0.034715222
-Ube2b.776	Ube2b	22210	LIB	776	0.058058259	0.051273228	0.06484329
-Ube2b.1626	Ube2b	22210	LIB	1626	0.068188614	0.039514731	0.096862497
-Ube2b.1661	Ube2b	22210	LIB	1661	0.499759711	0.928847363	0.070672059
-Ube2b.2075	Ube2b	22210	LIB	2075	0.330222156	0.308341814	0.352102499
-Ube2b.2079	Ube2b	22210	LIB	2079	2.317079085	1.318543552	3.315614618
-Ube2e1.228	Ube2e1	22194	LIB	228	0.029381966	0.058763931	0
-Ube2e1.858	Ube2e1	22194	LIB	858	1.993776879	3.221631126	0.765922632
-Ube2e1.1041	Ube2e1	22194	LIB	1041	1.358310257	1.871372176	0.845248338
-Ube2e1.1126	Ube2e1	22194	LIB	1126	0.041122487	0.005949233	0.07629574
-Ube2e1.1207	Ube2e1	22194	LIB	1207	0.58531289	0.718171988	0.452453792
-Ube2e1.1357	Ube2e1	22194	LIB	1357	0.28858651	0.211572207	0.365600814
-Ube2i.40	Ube2i	22196	LIB	40	0.497636722	0.420658059	0.574615385
-Ube2i.2212	Ube2i	22196	LIB	2212	1.277510212	1.011704567	1.543315856
-Ube2i.2447	Ube2i	22196	LIB	2447	0.048358827	0.096717655	0
-Ube2i.2498	Ube2i	22196	LIB	2498	1.139381303	0.697955118	1.580807487
-Usp22.1429	Usp22	216825	LIB	1429	0.478996919	0.42942241	0.528571429
-Usp22.2382	Usp22	216825	LIB	2382	0.111911328	0.109925123	0.113897532
-Usp22.2760	Usp22	216825	LIB	2760	0.061983148	0.031042902	0.092923394
-Usp22.3603	Usp22	216825	LIB	3603	NA	NA	NA
-Usp27x.1408	Usp27x	54651	LIB	1408	0.122921318	0.012626263	0.233216374
-Usp27x.2829	Usp27x	54651	LIB	2829	0.254051618	0.175833833	0.332269403
-Usp27x.2922	Usp27x	54651	LIB	2922	0.319959074	0.472527473	0.167390675
-Usp27x.3592	Usp27x	54651	LIB	3592	0.29489203	0.052753713	0.537030347
-Usp27x.3593	Usp27x	54651	LIB	3593	17.22570286	0.2671952	34.18421053
-Usp51.737	Usp51	635253	LIB	737	0.908903305	0.390760346	1.427046263
-Usp51.1997	Usp51	635253	LIB	1997	0.310486428	0.43330104	0.187671816
-Usp51.2109	Usp51	635253	LIB	2109	0.164332887	0.186081505	0.14258427
-Usp51.2114	Usp51	635253	LIB	2114	0.038897596	0.009535553	0.06825964
-Usp51.2194	Usp51	635253	LIB	2194	0.931503481	0.196846112	1.66616085
-Utx.652	Utx	22289	LIB	652	4.641855236	4.328129783	4.95558069
-Utx.888	Utx	22289	LIB	888	1.075866425	1.751019313	0.400713536
-Utx.1445	Utx	22289	LIB	1445	1.5705291	1.884518877	1.256539322
-Utx.4317	Utx	22289	LIB	4317	1.736188537	3.037108334	0.43526874
-Utx.4510	Utx	22289	LIB	4510	2.286589128	3.113532021	1.459646236
-Wbp7.2972	Wbp7	75410	LIB	2972	1.513599735	2.458444271	0.568755198
-Wbp7.3029	Wbp7	75410	LIB	3029	0.035307517	0	0.070615034
-Wbp7.5587	Wbp7	75410	LIB	5587	0	0	0
-Wbp7.6965	Wbp7	75410	LIB	6965	0	0	0
-Wdr5.501	Wdr5	140858	LIB	501	2.408515669	4.387538327	0.429493011
-Wdr5.502	Wdr5	140858	LIB	502	0.042069153	0.061053985	0.023084322
-Wdr5.1321	Wdr5	140858	LIB	1321	0.247222355	0.260246645	0.234198065
-Wdr5.1765	Wdr5	140858	LIB	1765	0	0	0
-Wdr5.2837	Wdr5	140858	LIB	2837	0.077594328	0.146670387	0.008518269
-Wdr82.1889	Wdr82	77305	LIB	1889	18.17214402	17.05537669	19.28891135
-Wdr82.3590	Wdr82	77305	LIB	3590	0.540832199	0.657836623	0.423827774
-Wdr82.3705	Wdr82	77305	LIB	3705	0.175116794	0.093333854	0.256899734
-Wdr82.4023	Wdr82	77305	LIB	4023	0.723659143	1.142793941	0.304524346
-Whsc1.812	Whsc1	107823	LIB	812	0.904200829	1.579513299	0.228888359
-Whsc1.818	Whsc1	107823	LIB	818	0.470434488	0.340148963	0.600720013
-Whsc1.3055	Whsc1	107823	LIB	3055	0.121372859	0.0001485	0.242597217
-Whsc1.3056	Whsc1	107823	LIB	3056	0.209818088	0.240167026	0.179469151
-Whsc1l1.276	Whsc1l1	234135	LIB	276	0.003690779	0.001781142	0.005600417
-Whsc1l1.373	Whsc1l1	234135	LIB	373	0.000537019	4.11E-05	0.001032946
-Whsc1l1.524	Whsc1l1	234135	LIB	524	1.108399963	1.304866171	0.911933755
-Whsc1l1.1307	Whsc1l1	234135	LIB	1307	0.11091394	0.105350477	0.116477403
-Whsc1l1.1653	Whsc1l1	234135	LIB	1653	0	0	0
-Wnt5a.2013	Wnt5a	22418	LIB	2013	0.364395259	0.140090029	0.588700489
-Wnt5a.2659	Wnt5a	22418	LIB	2659	0.746392031	0.784340702	0.708443359
-Wnt5a.2764	Wnt5a	22418	LIB	2764	0.057297605	0.114595211	0
-Wnt5a.4154	Wnt5a	22418	LIB	4154	1.074939471	1.697942922	0.45193602
--- a/tool_dependencies.xml	Mon Jan 19 22:08:26 2015 -0500
+++ /dev/null	Thu Jan 01 00:00:00 1970 +0000
@@ -1,29 +0,0 @@
-<?xml version="1.0"?>
-<tool_dependency>
-    <package name="R" version="3.1.2">
-        <repository changeset_revision="f0626dac6765" name="package_r_3_1_2" owner="iuc" prior_installation_required="True" toolshed="https://testtoolshed.g2.bx.psu.edu" />
-    </package>
-    <package name="shrnaseq_r" version="0.1">
-        <install version="1.0">
-            <actions>
-                <action type="setup_r_environment">
-                    <repository changeset_revision="f0626dac6765" name="package_r_3_1_2" owner="iuc" toolshed="https://testtoolshed.g2.bx.psu.edu">
-                        <package name="R" version="3.1.2" />
-                    </repository>
-                    <package>https://github.com/fubar2/galaxy_tool_source/blob/master/RELEASE_2_14/locfit_1.5-9.1.tar.gz?raw=true</package>
-                    <package>https://github.com/fubar2/galaxy_tool_source/blob/master/RELEASE_2_14/limma_3.22.4.tar.gz?raw=true</package>
-                    <package>https://github.com/fubar2/galaxy_tool_source/blob/master/RELEASE_2_14/edgeR_3.8.5.tar.gz?raw=true</package>
-                    <package>https://github.com/fubar2/galaxy_tool_source/blob/master/RELEASE_2_14/statmod_1.4.20.tar.gz?raw=true</package>
-                </action>
-                <action type="chmod">
-                    <file mode="755">$REPOSITORY_INSTALL_DIR/hairpinTool.R</file>            
-                </action>
-                <action type="set_environment">
-                    <environment_variable action="set_to" name="HAIRPINTOOL_R_SOURCE">$REPOSITORY_INSTALL_DIR/hairpinTool.R</environment_variable>
-                </action>
-            </actions>
-        </install>
-    </package>
-    <readme>
-    </readme>
-</tool_dependency>